cars 2019 rennes, france€¦ · rennes, france program. 3 jun 18–21 2019 ouven e acobin enne...

A journal for interdisciplinary research, development and applications of image guided

diagnosis and therapy

www.cars-int.orgwww.cars2019.org

COMPUTER ASSISTED RADIOLOGY AND SURGERY

CARS 2019

33rd International Congress and Exhibition

Main Themes Medical Imaging Computed Maxillofacial Imaging Image Processing and Visualization Multidisciplinary Computational Anatomy E-Health and IHE Computer Aided Diagnosis Computer Assisted Radiation Therapy Image and Model Guided Therapy Personalized Medicine Surgical Navigation Surgical Robotics and Instrumentation Surgical Simulation and Education Computer Assisted Orthopaedic and Spinal Surgery Computer Assisted Head and Neck, and ENT Surgery Image Guided Neurosurgery Minimally Invasive Cardiovascular and Thoracoabdominal Surgery Information Processing in Computer-Assisted Intervention Digital Operating Room Human-Machine Interface Pathology Informatics Machine Intelligence Integrated Patient Care Tumor Boards Innovative Clinical Investigations

CARS 2019 PresidentPierre Jannin, PhD (FR)

Congress Organizing Committee Christos Angelopoulos, DDS (US)Elizabeth Beckmann, BSc (GB)Leonard Berliner, MD (US)Ulrich Bick, MD (DE)Davide Caramella, MD (IT)Kevin Cleary, PhD (US)Mario A. Cypko, PhD (NL)Takeyoshi Dohi, PhD (JP)Kunio Doi, PhD (US)Volkmar Falk, MD, PhD (DE)Allan G. Farman, PhD, DSc (US)Hubertus Feussner, MD (DE)Guy Frija, MD (FR)Miguel Á. González Ballester, PhD (ES)Makoto Hashizume, MD, PhD, FACS (JP)Yoshihiko Hayakawa, PhD (JP)Javier Herrero Jover, MD, PhD (ES)David Hilderbrand (US)Pierre Jannin, PhD (FR)Leo Joskowicz, PhD (IL)Tina Kapur, PhD (US)Heinz U. Lemke, PhD (DE) (Chair)Kensaku Mori, PhD (JP)Hironobu Nakamura, MD, PhD (JP)Nassir Navab, PhD (DE)Terry M. Peters, PhD (CA)Osman M. Ratib, MD, PhD, FAHA (CH)Hans G. Ringertz, MD, PhD (SE)Yoshinobu Sato, PhD (JP)Ramin Shahidi, PhD (US)Akinobu Shimizu, PhD (JP)Hiroyuki Yoshida, PhD (US)

June 18–21, 2019Rennes, France

PROGRAM

3

June 18–21, 2019 | Le Couvent des Jacobins Rennes, France

CARS 2019 Content

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CARS 2019 Opening 10

12th CARS Clinical Day 11 Artificial Intelligence for Medical Imaging 11 Artificial Intelligence in Imaging for Surgery and Radiology 11 Innovations in Surgery 11 Panel Discussion: Artificial Intelligence in the Future of Radiology and Surgery 11

10th International Conference on Information Processing in Computer-Assisted Interventions (IPCAI) SP 1: Interventional Imaging 8 SP 2: Surgical Planning and Simulation, System and Software 8 SP 3: Tracking and Navigation 8 SP 4: Augmented Reality, Advanced Intraoperative Visualization, and User Interface 8 SP 5: Surgical Data Science 9 SP 6: Interventional Robotics, Evaluation and Validation 9 IPCAI Awards 9

33rd International Congress and Exhibition on Computer Assisted Radiology (CAR) Image-guided Therapy 14 Deep Learning for Image Processing 14 Image Registration and its Application 14 image Segmentation by Machine Learning (1) 16 Image Segmentation by Machine Learning (2) 16 Image Segmentation: Other Innovative Approaches 16 CAR / CAD-AI Joint Session on Deep Learning and GAN in Medical Imaging 18 Visualization and Augmented Reality 18 Image Analysis (1) 19 Image Analysis (2) 19 Decision Support, Prediction 19

Computer Assisted Radiology and Surgery (CARS) 21st IFCARS / SPIE / ISCAS Joint Workshop on the Digital Operating Room (DOR) 12 4th ISCAS / CAD-AI / IFCARS Joint Symposium on Multidisciplinary Computational Anatomy (MCA) 12 2nd Workshop on Digital Space Medicine (DSM) 12 Special Focus Session: ERC: Europe got talents 12 5th Young Investigators Networking Session (YINS) 16

23rd Annual Conference of the International Society for Computer Aided Surgery (ISCAS)

Surgical Robotics & Instrumentation 14 CAD-AI / ISCAS Joint Session on Artificial Intelligence in Computer-aided Diagnosis and Image-guided Therapy 14 Mixed reality for Surgical Simulation, Training and Education 16 Computational Methods for Image-guided Therapy 16 Image-guided Neuro-interventions and Applications 18 Rapid Prototyping Applications in Image-guided Therapy 18 Workflow Analysis and Modeling for Image-guided Therapy 18 Interventional Robotics for Orthopedics 19 Image-guided Orthopedic Interventions 19 Motion & Shape Tracking and Analysis for Image-guided Therapy 19

21st International Conference on Computer-Aided Diagnosis and Artificial Intelligence (CAD-AI)

CAD-AI / ISCAS Joint Session on Artificial Intelligence in Computer-aided Diagnosis and Image-guided Therapy 14 Deep Learning in Lung 1 15 Deep Learning in Abdomen 15 Deep Learning in Lung 2 17 Radiomics 1 17 Radiomics 2 17 Deep Learning in Breast, Eye, Brain, and MSK 17

25th Computed Maxillofacial Imaging Congress (CMI)

Surgical Navigation 13

Poster Sessions

Poster Sessions /Poster Presentation Times 20

Tutorials

TUT1: Tutorial AR/VR: Perceptual Capacities and Constraints in AR/VR for the visualization of 3D biomedical image data 25 TUT2: Tutorial SlicerIGT: Deep learning and computer vision for real-time procedure annotation 25 TUT4: Advanced Deep Learning for Medical Imaging Data 25 TUT3: Tutorial DL-1: Applied Deep Learning for Medical Scientists working with Image Data 25 TUT5: Hands-on tutorial on advanced Deep Learning for Medical Imaging 25

6th Surgetica

Modeling and simulation 26 Medical procedures: analysis and evaluation 26 Data fusion and augmented reality 26 Poster session 26 Robotics and mechatronics 27 Image processing and registration 27 Navigation and interventional planning 27

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CARS 2019 – 33rd International Congress and Exhibition

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General Information

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Purang Abolmaesumi, PhD (CA)Samir Aboul-Hosn, MD, PhD (ES)Reza Aghaeizadeh Zoroofi, PhD (IR)Asma‘a Al-Ekrish, MD (SA)Paul R. Algra, MD, PhD (NL)Russell J. Andrews, MD (US)Christos Angelopoulos, DDS (GR)Yoshinori Arai, PhD, DDS (JP)Jumpei Arata, PhD (JP)Eiichiro Ariji, DDS, PhD (JP)Paulo Mazzonicini Azevedo-Marques, PhD (BR)Frits H. Barneveld Binkhuysen, MD, PhD (NL)John S.H. Baxter, PhD (FR)Erwin Bellon, PhD (BE)Dirk Beyersdorff, MD (DE)Silvio Diego Bianchi, MD (IT)Ulrich Bick, MD (DE)Uldis Bite, MD (US)Mario Ceresa, PhD (ES)Kiyoyuki Chinzei, PhD (JP)Philippe Cinquin, MD, PhD (FR)Kevin Cleary, PhD (US)D. Louis Collins, PhD (CA)Marcos Costa Kurzhals, PhD (ES)Bernard L. Crowe, BA, MPH (AU)Mario A. Cypko, PhD (NL)Manuel Desco, PhD (ES)Andreas Dietz, MD, PhD (DE)Adrienn Dobai, MD (HU)Kunio Doi, PhD (US)André J. Duerinckx, MD, PhD (US)Georg Eggers, MD, DMD, PhD (DE)Randy E. Ellis, PhD (CA)Masahiro Endo, MD, PhD (JP)Uwe Engelmann, PhD (DE)Giuseppe Esposito, MD (US)Caroline Essert, PhD (FR)Allan G. Farman, PhD, DSc (US)Mansoor Fatehi, MD (IR)Josep Fernández-Bayó, PhD (ES)Gabor Fichtinger, PhD (CA)Martin Fiebich, PhD (DE)Michael Horst Friebe, PhD (DE)Masakatsu G. Fujie, PhD (JP)Hiroshi Fujita, PhD (JP)Shigekazu Fukuda, PhD (JP)Pablo Garcia Tahoces, PhD (ES)Bernard Gibaud, PhD (FR)Maryellen L. Giger, PhD (US)Enrique J. Gomez-Aguilera, PhD (ES)Miguel Ángel González Ballester, PhD (ES)Lixu Gu, PhD (CN)Horst K. Hahn, PhD (DE)Hideaki Haneishi, PhD (JP)Stefan Haßfeld, MD, MDS (DE)Yoshihiko Hayakawa, PhD (JP)Vicente Hernandez-Soler, MD, DDS, MPH, PhD (ES)Kenneth R. Hoffmann, PhD (US)Hiroshi Honda, MD, PhD (JP)Jaesung Hong, PhD (KR)Hidetaka Hontani, PhD (JP)Yimin Hu, PhD (CN)H.K. (Bernie) Huang, DSc, FRCR (Hon.) (US)Juan Antonio Hueto Madrid, MD (ES)Koji Ikuta, PhD (JP)Hiroshi Iseki, MD, PhD (JP)Masayori Ishikawa, PhD (JP)Hiroyasu Iso, MD (JP)Stephan Jacobs, MD (DE)Yulei Jiang, PhD (US)Nobuyuki Kanematsu, PhD (JP)Akitoshi Katsumata, DDS, PhD (JP)

Shigehiko Katsuragawa, PhD (JP)Zafrulla Khan, DDS, MS (US)Bob B. Kiaii, MD, FRCS (CA)Shoji Kido, MD, PhD (JP)Ron Kikinis, MD (US)Young Soo Kim, MD, PhD (KR)Yasutomi Kinosada, MD, PhD (JP)Masaki Kitajima, MD, PhD (JP)Etsuko Kobayashi, PhD (JP)Yo Kobayashi, PhD (JP)Cornelia Kober, PhD (DE)Yoshie Kodera, PhD (JP)Masahiko Koizumi, MD (JP)Christian Krettek, MD (DE)Tomohiro Kuroda, PhD (JP)Florent Lalys, PhD (FR)Heinz U. Lemke, PhD (DE)Lilian L.Y. Leong Fung, MBBS (HK)Qiang Li, PhD (CN)Hongen Liao, PhD (CN)Cristian A. Linte, PhD (US)Martin J. Lipton, MD, FACR, FACC (US)Brent J. Liu, PhD (US)Xiongbiao Luo, PhD (CN)Iván Maciá Oliver, PhD (ES)

Francisco Maculé Beneyto, MD (ES)Koutaro Maki, DDS, PhD (JP)Borut Marincek, MD (CH)Rüdiger Marmulla, MD (DE)Ken Masamune, PhD (JP)Yoshitaka Masutani, PhD (JP)Yasushi Matsumura, MD, PhD (JP)Andreas Melzer, MD, DDS (GB)Mamoru Mitsuishi, PhD (JP)Laureano Molins, MD, PhD (ES)Carlos Monserrat-Aranda, PhD (ES)Xavier Morandi, MD, PhD (FR)Kensaku Mori, PhD (JP)Parvin Mousavi, PhD (CA)Seong K. Mun, PhD (US)Yoshihiro Muragaki, MD, PhD (JP)Kikkeri Sitaramaiah Nagesh, MDS (IN)Janne J. Näppi, PhD (US)Valery Naranjo Ornedo, PhD (ES)Kwan-Hoong Ng, PhD (MY)Christopher Nimsky, MD (DE)Robert M. Nishikawa, PhD (US)Wieslaw L. Nowinski, PhD (SG)Fridtjof Nüsslin, PhD (DE)Steffen Oeltze-Jafra, PhD (DE)Isao Ohnishi, MD, PhD (JP)Yoshiharu Ohno, MD, PhD (JP)Minoru Ono, MD, PhD (JP)Kaan Orhan, DDS, PhD (TR)José Blas Pagador Carrasco, PhD (ES)Javier Pascau, PhD (ES)Ewa Pietka, PhD, DSc (PL)Andrea Pietrabissa, MD (IT)Andreas Pommert, PhD (DE)Henri Primo, MS (US)Jörg Raczkowsky, PhD (DE)Klaus Radermacher, PhD (DE)Stephen J. Riederer, PhD (US)Richard A. Robb, PhD (US)Maria José Rupérez-Moreno, PhD (ES)José Maria Sabater Navarro, PhD (ES)Hidetoshi Saitoh, PhD (JP)Luisa F. Sánchez Peralta, PhD (ES)Patricia Sánchez-González, PhD (ES)Warren S. Sandberg, MD, PhD (US)Duygu Sarikaya, PhD (FR)

Richard M. Satava, MD (US)Yoshinobu Sato, PhD (JP)Satoshi Sawada, MD (JP)Kurt Alexander Schicho, MD, PhD (AT)Wolfgang Schlegel, PhD (DE)Robert A. Schmidt, MD (US)Armin Schneider, PhD (DE)Alexander Schramm, MD, DDS, PhD (DE)Rainer Schubert, MD (AT)Dirk Schulze, PhD (DE)Achim Schweikard, PhD (DE)Ramin Shahidi, PhD (US)Mitsuo Shimada, MD, PhD (JP)Akinobu Shimizu, PhD (JP)Amber Simpson, PhD (US)Eduardo Soudah, PhD (ES)Stefanie Speidel, PhD (DE)Matthäus Stöhr, MD (DE)Geert J. Streekstra, PhD (NL)Nobuhiko Sugano, MD, PhD (JP)Kazuro Sugimura, MD (JP)Tae Suk Suh, PhD (KR)Iori Sumida, PhD (JP)Naoki Suzuki, MD, PhD (JP)Russell H. Taylor, PhD (US)Ulf K.-M. Teichgräber, MD, PhD (DE)Bart M. ter Haar Romeny, PhD (NL)Andrew E. Todd-Pokropek, PhD (GB)Klaus D. Toennies, PhD (DE)Thomas Tolxdorff, PhD (DE)Noriyuki Tomiyama, MD, PhD (JP)Fukai Toyofuku, PhD (JP)Jocelyne Troccaz, PhD (FR)Jayaram K. Udupa, PhD (US)Tamas Ungi, PhD (CA)Michiel W.M. van den Brekel, MD, PhD (NL)Eric vanSonnenberg, MD (US)Max A. Viergever, PhD (NL)Gabriele von Voigt, PhD (DE)Kirby G. Vosburgh, PhD (US)Shinichi Wada, PhD (JP)Andreas Wahle, PhD (US)Stefan Weber, PhD (CH)Thomas Wendler, PhD (DE)Michael Wich, MD (DE)Dirk Wilhelm, MD (DE)Takaharu Yamazaki, PhD (JP)Guang-Zhong Yang, PhD (GB)Byung-Ju Yi, PhD (KR)Hiroyuki Yoshida, PhD (US)Toshiki Yoshimine, MD (JP)

CARS 2019 Program Committee

VenueLe Couvent des Jacobins20 Place Sainte-Anne, 35000 Rennes, FRANCEwww.cars2019.org

CARS 2019 PresidentPierre Jannin, PhD (FR)INSERM Research DirectorLTSI, University of Rennes 1Email: [email protected]

Congress Organizing CommitteeChristos Angelopoulos, DDS (US)Elizabeth Beckmann, BSc (GB)Leonard Berliner, MD (US)Ulrich Bick, MD (DE)Davide Caramella, MD (IT)Kevin Cleary, PhD (US)Mario A. Cypko, PhD (NL)Takeyoshi Dohi, PhD (JP)Kunio Doi, PhD (US)Volkmar Falk, MD, PhD (DE)

Conference OrganizationCARS OrganizerProf. Heinz U. Lemke, PhDTechnical University of Berlin, DResearch Professor of RadiologyUniversity of Southern California, Los Angeles, USAInternational Foundation for CARSEmail: [email protected]

CARS Conference OfficeMrs. Franziska SchweikertKlettgaustraße 2079790 Kuessaberg, GermanyTel.: +49 (0) 7742 922 434Email: [email protected]

Allan G. Farman, PhD, DSc (US)Hubertus Feussner, MD (DE)Guy Frija, MD (FR)Miguel Á. González Ballester, PhD (ES)Makoto Hashizume, MD, PhD, FACS (JP)Yoshihiko Hayakawa, PhD (JP)Javier Herrero Jover, MD, PhD (ES)David Hilderbrand (US)Pierre Jannin, PhD (FR)Leo Joskowicz, PhD (IL)Tina Kapur, PhD (US)Heinz U. Lemke, PhD (DE) (Chair) Kensaku Mori, PhD (JP)Hironobu Nakamura, MD, PhD (JP)Nassir Navab, PhD (DE)Terry M. Peters, PhD (CA)Osman M. Ratib, MD, PhD, FAHA (CH)Hans G. Ringertz, MD, PhD (SE)Yoshinobu Sato, PhD (JP)Ramin Shahidi, PhD (US)Akinobu Shimizu, PhD (JP)Hiroyuki Yoshida, PhD (US)

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Program General Information

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INTERNET ACCESSComplimentary wireless access available; instruc-tions will be posted on site.

Food and Beverage ServicesCOFFEE BREAKSComplimentary coffee will be served each day of the conference.Monday–Tuesday.................................08:00–08:30 Wednesday–Friday .............................. 07:30–08:00Monday–Friday ....................................10:00–10:30 Monday–Friday ....................................15:30–16:00

HOSTED LUNCHEONSCARS 2019 hosted luncheons are included in regis-tration packets for all registrants including students.Monday–Friday ....................................12:30–13:30

LOCATIONSMonday–Wednesday ................. Gallerie and CloitreThursday–Friday .................Exhibition space Halle 0

Author / Presenter Information

SPEAKER CHECK-IN AND PREVIEW ROOMRoom Salle 7Tuesday-Thursday .................................07:30–18:30Friday ...................................................07:30–17:00

All presenters must stop by Speaker Check-In to upload their file(s) at least two hours before their scheduled talk. Authors are not able to present using their own devices. All conference rooms have a laptop, projector, screen, lapel microphone, and laser pointer.

LONG ORAL PRESENTATION INSTRUCTIONSEach regular and invited oral presentation is alloca-ted a 15 minute slot:Regular talks must not exceed 12 minutes, leaving 2-3 minutes for questions.Timing will be strictly enforced to ensure a smooth handover between speakers. As a rule of thumb, you should have one slide per minute of talk time. The session chair will introduce each speaker and title of the talk.

POSTER INSTRUCTIONSAtrium and Halle 0Poster format: A0 - Portrait

Poster set-up and dismantling timesSurgeticaAuthor Poster Setup Time .......Monday, 10:00–10:30Authors Remove Posters ........Tuesday, 12:00–13:30

IPCAIAuthor Poster Setup Time ........Monday 10:00–10:30and ....................................... Tuesday 07:30–08:30Authors Remove Posters ............ Friday 17:15–18:00

CAR/CARS/ISCAS/CAD-AI/CMIAuthor Poster Setup Time ...Wednesday 07:00-08:30Authors Remove Posters ............. Friday 17:15–18:00

For updated information, please register to the CARS 2019 newsletter on the CARS 2019 website or follow us on Facebook and Twitter.

HoursRegistration desk will be located at the entrance of the Couvent des Jacobins Conference Center.The registration desk will be opened on:17 June 2019, Monday .........................07:00–19:0018 June 2019, Tuesday ........................07:00–19:0019 June 2019, Wednesday ...................07:00–19:0020 June 2019, Thursday .......................07:00–19:0021 June 2019, Friday ...........................07:30–18:00

Exhibition-Opening HoursHalle 019 June 2019, Wednesday .................. 18:00–20:0020 June 2019, Thursday ......................08:00–20:0021 June 2019, Friday ...........................08:00–17:00

CONFERENCE REGISTRATIONIncludes admission to all conference sessions, plenaries, panels, and poster sessions, receptions, luncheons, coffee breaks, 3-day free public trans-portation.

TUTORIAL REGISTRATIONTutorials are priced separately. Tutorial-only regis-tration includes your selected tutorial(s), tutorial notes, and coffee breaks. Course prices include applicable taxes. Onsite, please go to the registrati-on desk after picking up your badge.

AccessCARS booths will be available at your arrival at the Rennes airport and railway station to welcome you at your arrival.Opening hours:17 June 2019, Monday .........................17:00–19:00

Currency & ATMsThe Euro is the official currency of France. You can pay everywhere with cash or bank card.

POSTER SESSION INSTRUCTIONSA poster author or coauthor is required to stand by the poster during the scheduled poster sessions to answer questions from attendees. Schedules depend on the conference track (see poster list).

Presenters who have not placed their poster(s) on their assigned board by 30 minutes prior to the session on the day of their presentation will be considered a “no show”.

CAR/CARSPoster session ............ Thursday–Friday 10:00–11:15

ISCASPoster session ........... Thursday–Friday, 10:00–11:15

IPCAIPoster session ........................Tuesday, 12:00–13:30Poster session ........................Tuesday, 15:30–17:00Poster session ...................Wednesday, 12:30–13:30Poster session ...................Wednesday, 15:30–17:30

CAD-AIPoster session .......................Thursday, 10:00–11:15

CMIAuthors will present main findings of their paper in a 5’ presentation in the corresponding CMI interactive sessionPoster session ...................Wednesday, 14:45–15:30

Code of ConductCARS 2019 is committed to providing a harass-ment- and discrimination-free experience for everyo-ne at our events, an experience that embraces the richness of diversity where participants may exchange ideas, learn, network, and socialize in the company of colleagues in an environment of mutual respect.CARS 2019 does not tolerate harassment of event participants, attendees, exhibitors, speakers, volun-teers, contractors, service providers, venue staff, or CARS 2019 staff. This Code of Conduct applies to all CARS 2019 meeting-related events, including those sponsored by other organizations but hosted by CARS 2019, in public or private facilities.

SustainabilityCARS 2019 is making a special effort toward sustainability. Different actions are conducted in this direction. Food is mainly organic and coming from local producers. Food waste will be donated to as-sociations. Electronic program is available this year and printed programs will be available only for those who would like to have a copy. We were not able to avoid printed proceedings this year. No bags, please bring your own. Tickets for public transportation are made freely available to each attendee. Please follow our efforts.

Reporting of Unethical or Inappropriate BehaviorAt CARS 2019, contact any CARS Staff with con-cerns or questions for thorough follow-up. If you feel in immediate danger, please dial the local emergen-cy number for police intervention (112). CARS 2019 has established a confidential reporting system for staff and all meetings participants to raise concerns about possible unethical or inappropriate behavior within our community. Complaints may be filed by sending an email at [email protected]

Recording PolicyConferences, workshops, tutorials, and poster sessi-ons: Presenters give right to CARS 2019 to record presentations including slides content, audio and video and possibly to make them available on-line. A consent form will be signed when uploading the files in the speaker check-in room. Any other recording of any kind is prohibited without prior written consent of the presenter or instructor. Attendees may not capture or use materials presented in any meeting/course room or in course notes on display without written permission.

No-Smoking PolicySmoking, including e-cigarettes, is not permitted at any CARS 2019 event.

Updated program information are available at www.cars2019.org/schedule.

CARS 2019 has achieved 32 CPD credits for full attendance in accordance with the CPD Scheme of the Royal College of Radiologists (UK).

No liability can be accepted for any errors. The program is subject to alteration.

The Rennes Tourism Office is located in the conference center at the same level.

Rennes, the Capital of BrittanyRennes‘ history can be traced back for over two thousand years, with the Redones, a Gallic tribe who founded their chief township on the confluence of the Ille and Vilaine rivers. Conquered by the Romans in 52 B.C.E., the town was renamed Condate Riedonum, the city of the Redones, and although the word Condate has been dropped over the centuries, Riedonum remains the root of Rennes. Parts of the ancient Gallo-Roman city walls can still be seen today!

During the Fall of the Roman Empire, Rennes and the remainder of the modern day region of Brittany, were the last bulwark of the Roman Empire against the invading Frankish tribes led by Clovis 1, the first King of the Franks, deemed by Charles de Gaulle as „the first king of what would become France.“

However, by the 5th century, the Bretons migrating from modern day Wales and Cornwall had occupied the western portion of the peninsula, giving it the name Brittany, while the Franks occupied the eastern portion. To ease tensions between the two, the Breton March was created, a region between the two which included Rennes. In 851, Rennes had been absorbed into the Brittany with the remainder of the Breton March doing so over the course of the 9th century.

During the Medieval period, Brittany enjoyed a relatively large degree of autonomy as a feudal duchy, ruled by a Duke or Duchess. Often, the Duchy of Brittany found itself on opposing sides in Franco- English conflicts. This autonomy, however, came to an end with the „Mad War“ of 1485, in which the Duchy of Brittany, allied with the Kingdom of England, waged war against France. The war ended in 1488, and one year later, Duchess Anne of Brittany was engaged to King Charles VIII of France in Rennes, making the merger of the two families and the end of Brittany as an independent state.

Rennes and Brittany continued to thrive under the rule of the French monarchs, ending with the French Revolution. During this tumultuous century, many of Rennes architectural landmarks including the Palace of Commerce, Opera and the Fine Arts Museum were constructed, with large modifications made to existing buildings such as the City Hall and Parliament of Brittany, giving Rennes its imperial splendour. Although heavily bombarded by both sides during World War II, Rennes survived and in the eight decades since, has been one of the fastest growing cities in France, known for its livability, distinct culture, and technological innovation.

Our Venue – Le Couvent des Jacobins

Le Couvent des Jacobins was a Dominican convent in the centre of Rennes founded in 1369 under the patronage of John of Montfort, or John XI Duke of Brittany. Situated in Place Sainte-Anne, now the heart of downtown Rennes, the location originally lay outside Rennes medieval walls. The convent quickly became part of the fabric of Rennes‘ religious life, which culminated with the celebration of Duchess Anne of Brittany‘s engagement to King Charles VIII, unifying Brittany and France.

However, Le Couvent des Jacobins‘ days were numbered as a religious institution as the French Revolution arrived in 1789 and with it, the seizure of church properties by the state. By 1793, the buildings were assigned to the French army, in whose possession they would remain for over two centuries.

In 1991, Le Couvent des Jacobins received official classification as a historic building, and in 2002, it became the property of the City of Rennes, who transformed it into the contemporary conference centre that we see today.


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8

Tuesday, June 18, 2019 Wednesday, June 19, 2019

10:30 Short Podium Presentation 3: Tracking and NavigationSession Chair: Stamatia Giannarou, PhD (GB)

Limits of Electromagnetic Tracking for High Precision InterventionsD. Kügler, H. Krumb, J. Bredemann, I. Stenin, J. Kristin, T. Klenzner, J. Schipper, R. Schmitt, G. Sakas, A. Mukhopadhya, Technische Universität Darmstadt (DE) [TN-1-06]

Flexible Needle and Patient Tracking using Fractional Scanning for Reduced Dose in Interventional CT ProceduresL. Joskowicz, G. Medan, Hebrew University of Jerusalem (IL) [TN-2-07]

Deformable Multi-Modal Registration for Navigation in Beating-Heart Cardiac SurgeryJ. Peoples, G. Bisleri, R. Ellis, Queen‘s University (CA) [TN-3-18]

Immersive Virtual Reality Environment for MedicineL. Groves, P. Carnahan, D. Allen, T. Peters, E. Chen, Robarts Research Institute (CA) [TN-4-20]

Learning Soft-Tissue Behavior of Organs for Surgical Navigation with Convolutional Neural NetworksM. Pfeiffer, C. Riediger, J. Weitz, S. Speidel, NCT Dresden (DE) [TN-5-65]

On the Feasibility of 3D/4D Ultrasound Transperineal Image-Guidance for Robotic Radical ProstatectomyP. Mathur, G. Samei, K. Tsang, J. Lobo, S. Salcudean, University of British Columbia (CA) [TN-6-84]

11:15 Short Podium Presentation 4: Augmented Reality, Advanced Intraoperative Visualization and User Interface Session Chair: Marta Kersten, PhD (CA)

Interactive Flying Frustums (IFFs): Spatially-Aware Surgical Data VisualizationJ. Fotouhi, M. Unberath, T. Song, W. Gu, A. Johnson, G. Osgood, M. Armand, N. Navab, Johns Hopkins University (US) [AU-1-12]

Pedicle Screw Navigation using Surface Registration on the Microsoft HoloLensF. Liebmann, S. Roner, M. von Atzigen, D. Scaramuzza, R. Sutter, J. Snedeker, M. Farshad, P. Fürnstahl, Balgrist University Hospital Zurich (CH) [AU-2-75]

Automatic tissue classification in textured models: A novel approach to intraoperative integration of structured light scanningB. Chan, J. Auyeung, J. Rudan, P. Mousavi, M. Kunz, Queen‘s University (CA) [AU-3-19]

A Novel Gaze-supported Multimodel Human Computer Interaction for Ultrasound MachinesH. Zhu, S. Salcudean, R. Rohling, University of British Columbia (CA) [AU-4-23]

Deep Neural Maps for Unsupervised Visualization of High Grade Cancer in Prostate BiopsiesA. Sedghi, M. Pesteie, S. Azizi, G. Javadi, P. Yan, S. Xu, J.T. Kwak, P. Pinto, I.B. Turkbey, P. Choyke, B. Wood, R. Rohling, P. Abolmaesumi, P. Mousavi, Queen’s University (CA) [AU-5-59]

A „Pick-Up“ Stereoscopic Camera with Visual-Motor Aligned Control for the da Vinci Surgical System: A Preliminary StudyA. Avinash, A.E. Abdelaal, P. Mathur, S. Salcudean, University of British Columbia (CA) [AU-6-78]

12:00 Lunch Break and Poster Session I

8:30 Welcome/Opening for IPCAI 2019Program Chairs: Raphael Sznitman, Kanako Harada, Elvis Chen

8:40 Short Podium Presentation 1: Interventional ImagingSession Chair: Ilker Hacihaliloglu, PhD (US)

Towards Intraoperative Use of Ambient Mass Spectrometry Imaging for Cardiac TissueR. Ellis, D. Tomalty, A. Santilli, J. Rudan, M. Kaufmann, G. Bisleri, Queen’s University (CA) [II-1-08]

Learning Needle Tip Localization from Digital Subtraction in 2D UltrasoundC. Mwikirize, J.L. Nosher, I. Hacihaliloglu, Rutgers University (US) [II-2-11]

Catheter Localization in 3D Ultrasound Using Voxel-of-Interest-based ConvNets for Cardiac Intervention H. Yang, C. Shan, A.F. Kolen, P. H. N. de With, Eindhoven University of Technology (NL) [II-3-36]

Uncertainty-aware Performance Assessment of Optical Imaging Modalities with Invertible Neural NetworksT. Adler, L. Ardizzone, A. Vemuri, J. Groehl, T. Kirchner, L. Ayala, S. Wirkert, J. Kruse, C. Rother, U. Köthe, L. Mair-Hein, DKFZ Heidelberg (DE), [II-4-57]

Implicit Domain Adaptation with Conditional Generative Adversarial Networks for Depth Prediction in EndoscopyA. Rau, P. Edwards, O. Ahmad, P. Riordan, M. Janatka, L. Lovat, D. Stoyanov, University College London (GB) [II-5-72]

Estimation of Tissue Oxygen Saturation based on Image to Image TranslationQ. Li, J. Lin, N. Clancy, D. Elson, Imperial College London (GB) [II-6-92]

09:20 Short Podium Presentation 2: Surgical Planning and Simulation, System and SoftwareSession Chair: Caroline Essert, PhD (FR)

Flexible and Comprehensive Patient-Specific Mitral Valve Silicone Models with Chordae Tendinae Made From 3D-Printable MoldsS. Engelhardt, B. Preim, M. Karck, I. Wolf, R. De Simone, S. Sauerzapf, University of Applied Sciences Mannheim (DE) [SS-1-02]

Towards an Automatic Preoperative Pipeline for Image-Guided Temporal Bone SurgeryJ. Fauser, I. Stenin, Markus Bauer, W.-H. Hsu, J. Kristin, T. Klenzner, J. Schipper, A. Mukhopadhyay, TU Darmstadt (DE) [SS-2-27]

Dynamic, Patient-Specific Mitral Valve Modelling for Percutaneous Valve Repair PlanningO. Ginty, J. Moore, P. Carnahan, M. Eskandari, M. Monaghan, T. Peters, Robarts Research Institude, (CA) [SS-3-35]

Automatic Biplane Left Ventricular Ejection Fraction Estimation with Mobile Point-of-care Ultrasound Using Multi-task Learning and Adversarial TrainingM. Jafari, H. Girgis, N. Van Woudenberg, Z. Liao, R. Rohling, K. Gin, P. Abolmaesumi, T. Tsang, University of British Columbia (CA) [SS-4-43]

Prediction of Laparoscopic Procedure Duration Using Unlabeled, Multimodal Sensor DataS. Bodenstedt, M. Wagner, L. Mündermann, H. Kenngott, B. Müller-Stich, S. Torge Mees, J. Weitz, S. Speidel, NCT Dresden (DE) [SS-5-61]

10:00 Coffee Break and Poster Session

13:30 Short Podium Presentation 5: Surgical Data ScienceSession Chair: Nicola Rieke, PhD (DE)

Weakly Supervised Method for Spatio-Temporal Tool Tracking in Laparoscopic VideosC. Nwoye, D. Mutter, J. Marescaux, N. Padoy, University of Strasbourg (FR) [SDS-1-26]

Teacher/Student Approach for Semi-Supervised Surgical Phase RecognitionT. Yu, D. Mutter, J. Marescaux, N. Padoy, University of Strasbourg (FR) [SDS-2-32]

Objective Assessment of Intraoperative Technical Skill in Capsulorhexis with Temporal Neural NetworksT.S. Kim, M. O‘Brien, S. Zafar, G.D. Hager, S. Sikder, S. S. Vedula, Johns Hopkins University [SDS-3-44]

Visual Domain Adaptation with Self-Training for Face Detection in the Operating RoomT. Issenhuth, V. Srivastav, A. Gangi, N. Padoy, CAMMA (FR) [SDS-4-60]

Active Learning using Deep Bayesian Networks for Surgical Workflow AnalysisS. Bodenstedt, D. Rivoir, A. Jenke, M. Wagner, S.T. Mees, J. Weitz, S. Speidel, NCT Dresden (DE) [SDS-5-68]

Video-based Surgical Skill Assessment using Deep Neural NetworksI. Funke, S.T. Mees, J. Weitz, S. Speidel, NCT Dresden (DE) [SDS-6-76]

14:15 Short Podium Presentation 6: Interventional Robotics, Evaluation and Validation Session Chair: Amber Simpson, PhD (CA)

Design Optimization of A Contact-Aided Continuum Robot for Endobronchial Interventions Based on Anatomical ConstraintsL. Ros Freixedes, A. Gao, N. Liu. G.-Z. Yang, Imperial College London (GB) [RV-1-63]

Preliminary Study of An RNN Based Active Interventional Robotic System (AIRS) in Retinal MicrosurgeryC. He, I. Iordachita, Johns Hopkins University (USA) [RV-2-102]

Leveraging RSF and PET Images for Prognosis of Multiple Myeloma at DiagnosisL. Morvan, T. Carlier, C. Bailly, B. Jamet, C. Bodet-Milin, F. Kraeber-Bodéré, P. Moreau, C. Touzeau, D. Mateus, CRCINA INSERM (FR) [RV-3-24]

An In-vivo Porcine Dataset and Evaluation Methodology to Measure Soft-Body Laparoscopic Liver Registration Accuracy with an Extended Algorithm that Handles CollisionsR. Modrzejewski, T. Collins, B. Seeliger, A. Bartoli, A. Hostettler, J. Marescaux, IHU Stras-bourg (FR) [RV-4-28]

Fully Auto Automatic Self-gated 4D-MRI Construction from Free-breathing 2D Acquisitions Applied on Liver ImagesL. Vazquez Romaguera, N. Olofsson, R. Plantefeve, E. Lugez, J. De Guise, S. Kadoury, École Polytechnique de Montreal (CA) [RV-5-16]

15:00 IPCAI Awards 1 Session Chairs: Elvis Chen, PhD (CA), Kanako Harada (JP), Raphael Sznitman (CH)

15:30 Coffee Break and Poster Session 2

IPCAI 2019 – 10th International Conference on Information Processing in Computer-Assisted InterventionsGeneral Chairs: K. Mori, PhD (JP), P. Mousavi, PhD (CA), L. Maier-Hein, PhD (DE)

Room la Nef Room la Nef

08:00 Selected Podium Presentation 1: Interventional Imaging, Surgical Planning and Simulation, System and Software, Tracking and NavigationSession Chairs: Ingerid Reinersten, PhD (NO), Toby Collins, PhD (FR)

6 Audience-Chosen Presentations (20 minutes each)


10:30 Selected Podium Presentation 2: Augmented Reality, Advanced Intraoperative Visualization and User Interface, Surgical Data Science, Interventional Robotics, Evaluation and Validation Session Chairs: Danail Stoyanov, PhD (GB), Matthieu Chabanas, PhD (FR)

6 Audience-Chosen Presentations (20 minutes each)

12:30 Lunch Break and Poster Session 3

13:30 Short Presentation: Long AbstractsSession Chair: Cristian A. Linte, PhD (US)

Localizing Dexterous Surgical Tools in X-ray for Image-based NavigationC. Gao, M. Unberath, R. Taylor, M. Armand, Johns Hopkins University (USA) [LA-1]

Evaluation of Head Segmentation Quality for Treatment Planning of Tumor Treating Fields in Brain TumorsR. Shamir, Z. Bomzon, Novocure (IL) [LA-2]

Psychophysiological Data and Computer Vision to Assess Cognitive Load and Team Dynamics in Cardiac SurgeryR.D. Dias, S. Yule, L. Kennedy-Metz, M. Zenati, Harvard Medical School (US) [LA-3]

Unity and VTK for VR Medical Image Analysis – an Initial Clinical EvaluationG. Wheeler, S. Deng, N. Toussaint, K. Pushparajah, J. Schnabel, T. Peters, J. Simpson, A. Gomez, King‘s College London (GB) [LA-4]

EM Navigation of a Raman Spectroscopy Needle for Prostate Cancer Confirmation: Preliminary ex-vivo Study in 3D SlicerR. Shams, F. Picot, G. Sheehy, C. Menard, J.-F. Carrier, F. Leblond, S. Kadoury, Polytech-nique Montreal (CA) [LA-5]

Combining Visual Cues and Interactions for 3D-2D Registration in Liver LaparoscopyY.E. Lopez, E. Özgür, L. Calvet, B. Le Roy, E. Buc, A. Bartoli, Université Clermont-Auvergne (FR) [LA-6]

Novel Instrument Design for Electromagnetic Navigation BronchoscopyH. Jaeger, S. Hinds, T. Langø, E.F. Hofstad, O.V. Solberg, H. Leira, J. Scheltes, P. Cantillon-Murphy, University College Cork (IE) [LA-7]

OP 4.1: A User-Centered Platform for the Operation Room of the FutureK. März ;L. Maier-Hein, DKFZ (DE) [LA-8]

EchoBot: An Open-Source Robotic Ultrasound SystemA. Østvik, L. Bo, E. Smistad, SINTEF / NTNU (NO) [LA-9]

3D Ultrasound Image Guidance System for Focal Liver Tumor TherapiesD. Gillies, J. Bax, K. Barker, L. Gardi, D. Tessier, N. Kakani, A. Fenster, Robarts Research Institute (CA) [LA-10]

Miniature C-arm Simulator Using Wireless Accelerometer Based TrackingD. Allen, T. Peters, C. Clarkes, E. Chen, Robarts Research Institute (CA) [LA-11]

14:30 Plenary Discussion 15:00 IPCAI Awards II and ClosingSession Chairs: Raphael Sznitman, PhD (CH), Kanako Harada, PhD (JP), Elvis C.S. Chen, PhD (CA)


18:00 CARS 2019 Exhibition Opening Ceremony

IPCAI 2019 – 10th International Conference on Information Processing in Computer-Assisted InterventionsGeneral Chairs: K. Mori, PhD (JP), P. Mousavi, PhD (CA), L. Maier-Hein, PhD (DE)

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Tuesday, June 18, 2019 17:30 – 20:00 Wednesday, June 19, 2019 8:30 – 17:00

12th CARS Clinical Day Artificial Intelligence in Clinical Practice: Success and ChallengesChairs: Leonard Berliner, MD (US), Eric vanSonnenberg, MD (US), Hubertus Feussner, MD (DE), Pierre Jannin, PhD (FR)

8:30 Artificial Intelligence for Medical ImagingSession Chairs: Leonard Berliner, MD (US), Eric vanSonnenberg, MD (US)

8:30 Preparing students and practitioners for artificial intelligence: imperatives in medical educationInvited Speaker: Eric vanSonnenberg, MD, Univ. of Arizona College of Medicine; David Geffen School of Medicine at UCLA, CA (US)

8:45 Radiomics and radiogenomics: clinical applicationsInvited Speaker: Amber Simpson, PhD, Memorial Sloan Kettering Cancer Center, New York, NY (US)

9:00 Artificial intelligence in medical imaging: perspective from the NIHInvited Speaker: Krishna Kandarpa, MD, PhD, National Institutes of Health, Bethesda, MD (US)

9:15 Laparoscopic video image analysis: automated annotation with artificial intelligenceInvited Speaker: Masaaki Ito, MD, National Cancer Center East, Kashiwa (JP)

9:30 The impact of needle placement error and preoperative planning in prostate focal cryoablation: A simulation study P. Moreira, K. Tuncali, C. Tempany, J. Tokuda, Brigham and Women’s Hosp., Harvard Medical School, Boston, MA (US) [19-00094]

9:45 A Comparison of Thin Plate Spline Deformation and Finite Element Modeling for Brain Shift Compensation using Sparse Features that were Automatically Generated from 3D Intraoperative Ultrasound S. Frisken, M. Luo, A. Bunevicius, I. Machado, P. Juvekar, P. Unadkat, M. M. Bertotti, M. Toews, W. M. Wells, M. I. Miga, A. J. Golby, Brigham and Women’s Hosp., Boston, MA; Vanderbilt Univ., Nashville, TN (US); Univ. of Lisbon (PT); Ecole de Technologie Superieure, Montreal, QC (CA) [19-00054]

10:00 Coffee Break

10:30 Artificial Intelligence in Imaging for Surgery and RadiologySession Chairs: Krishna Kandarpa, MD (US), Giuseppe Esposito, MD (US)

10:30 Stanley-Baum-Lecture Artificial intelligence in radiology: A Path for the Democratization of AI in Radiological PracticeKeynote Speaker: Bibb Allen, Jr., MD, ACR’s Data Science Institute (USA)

11:00 Artificial intelligence in nuclear medicineInvited Speaker: Giuseppe Esposito, MD, Georgetown Univ. Medical Center, Washington, DC (US)

11:15 Detection and grading of sacroiliitis in computed tomography as incidental finding using deep learningInvited Speaker: Leo Joskowicz, PhD, The Hebrew University of Jerusalem (IL)

11:30 Early Interception of Lung Cancer through Artificial IntelligenceInvited Speaker: Michael Brady, PhD, University of Oxford (GB)

11:45 Assessment of surgical skills by using surgical navigation in robot- assisted partial nephrectomy S. Kobayashi, B. Cho, A. Huaulmé, K. Tatsugami, H. Honda, P. Jannin, M. Hashizume, M. Eto, Kyushu Univ.; Kyushu Univ. Hosp., Fukuoka (JP); Univ. of Rennes 1 (FR) [19-00012]

12:00 GPU-accelerated blood vessel enhancement from free-breathing angiogra-phy using robust principal component analysis M. Kawabe, Y. Kokura, T. Ohnishi, K. Nakano, H. Kato, Y. Ooka, T. Sakai, H. Haneishi, Chiba Univ.; Chiba Univ. Hosp.; Nagasaki Univ. (JP) [34]

12:15 Panel Discussion

12:30 Lunch Break

13:30 Innovations in SurgerySession Chairs: Hubertus Feussner, MD (DE), Leonard Berliner, MD (US)

13:30 SurgineeringInvited Speaker: Hubertus Feussner, MD, Technical Univ. of Munich (DE)

13:45 Potential Applications of artificial intelligence in surgeryInvited Speaker: Dirk Wilhelm, MD, Technical Univ. of Munich (DE)

14:00 The Future of Image Guided Surgery Invited Speaker: Richard Satava, MD, University of Washington, Seattle (US)

14:15 The future of surgery is flexible and image guidedInvited Speaker: Silvana Perretta, PhD, MD, University Hospital (NHC), Strasbourg (FR)

14:30 Surgical data science for functional neurosurgery Invited Speaker: Claire Haegelen, PhD, MD, University Hospital Rennes (FR)

14:45 Robotics and surgical data science in urologyInvited Speaker: Charles-Karim Bensalah, PhD, MD, University Hospital Rennes (FR)

15:00 Intra-arterial CT imaging during liver ablation treatment as an adjunct for accurate targeting and therapy monitoring – a feasibility study G. Chintalapani, E. Lin, R. Avritscher, B. Odisio, Siemens Medical Solutions USA Inc., Hoff-man Estates, IL; The Univ. of Texas MD Anderson Cancer Center, Houston, TX (US) [230]

15:15 A platform for irreversible electroporation treatment planning E. Perera-Bel, A. Ivorra, M. A. González Ballester, Univ. Pompeu Fabra, Barcelona (ES) [160]

15:30 Coffee Break

16:00 Panel Discussion: Artificial Intelligence in the Future of Radiology and SurgeryChairs: Leonard Berliner, MD (US), Eric vanSonnenberg, MD (US), Hubertus Feussner, MD (DE)

Introduction to Panel DiscussionLeonard Berliner, MD, New York Presbyterian-Brooklyn Methodist Hosp., Weill Cornell Medical College; Brooklyn, NY (US)

Participants:Amber Simpson, PhD (US), Krishna Kandarpa, MD, PhD (US), Masaaki Ito, MD (JP), Giuseppe Esposito, MD (US) Leo Joskowicz, PhD (IL), Michael Brady, PhD (GB), Bibb Allen, Jr. MD (US), Pierre Jannin, PhD (FR), Dirk Wilhelm, MD (DE), Richard Satava, MD (US)

17:00 End of Session


Room Le Réfectoire

CARS Computer Assisted Radiology and Surgery

CARS 2019 Opening

17:30 WelcomePierre Jannin, PhDPresident CARS 2019

Keynote Lectures:Fostering a Strong Ecosystem For Artificial Intelligence In Medical Imaging Bibb Allen Jr., MD, FACR Chief Medical Officer, American College of Radiology, Data Science Institute, Diagnos-tic Radiology, Grandview Medical Center, Birmingham, Alabama USA

Quantitative and Intelligent Imaging for Clinical Decision SupportSir Michael Brady, FRS, FREng, FMedSci, Membre Étranger de l’Académie des Sciences, Emeritus Professor of Oncologi-cal Imaging, University of Oxford, GB, Founder Chairman: Perspectum Diagnostics, ScreenPoint Medical, Founder Director: Mirada Medical, Volpara Health Technologies, Chairman: Optellum

19:00 CARS 2019 Opening Ceremony

Room La Nef

CARS 2019 Opening Ceremony

La Nef Tuesday, June 18th 2019 17:30–19:00Keynote Addresses

Fostering a Strong Ecosystem For Artifi-cial Intelligence In Medical ImagingFueled by the ever-increasing amount of data ge-nerated by the healthcare system applications for artificial intelligence in healthcare, especially wi-thin diagnostic imaging, are rapidly proliferating. Currently, no well-defined framework exists for determining how great ideas for AI algorithms in healthcare will advance from development to inte-grated clinical practice. Healthcare stakeholders including physicians, patients, medical societies, hospital systems, software developers, the health information technology industry and governmen-tal regulatory agencies all comprise a community that will need to function as an ecosystem system in order for AI algorithms to be deployed, monito-red, and improved in widespread clinical practice. Radiologists can play an important role in promo-ting this AI ecosystem by delineating structured AI use cases for diagnostic imaging and standar-dizing data elements and workflow integration interfaces. By developing structured AI use cases based on the needs of the physician community, radiologists and radiology specialty societies can assist developers in creating the tools that will advance the practice of medicine. If these use cases specify how datasets for algorithm training, testing and validation can be developed as well as specifying parameters for clinical integration and pathways for assessing algorithm performance in clinical practice, the likelihood of bringing safe and effective algorithms to clinical practice will increase dramatically. The development of an ac-tive AI ecosystem will facilitate the development and deployment of AI tools for healthcare that will help physicians solve medicine’s important problems.

Quantitative and Intelligent Imaging for Clinical Decision Support A number of important developments in CARS will be discussed primarily by reference to innovations in some of the medical image ana-lysis companies of which I am a Founder. First, image analysis can be quantitative, each pixel measuring a physical quantity. We first illustrate this by quantitative MRI of the liver, measuring proton density fat fraction; iron content; and fibroinflammation (units of time). This is applied to (non-alcoholic) fatty liver disease, steatohe-patitis (NASH), and therapeutic interventions, both measuring the effect of anti-NASH drugs and supporting liver surgery. Then, we show how breast density may be measured and applied to estimate x-ray dose in mammogra-phy. Second, image analysis can be intelligent based on methods developed in AI and Machine Learning. We illustrate this both in MRI analysis of the liver and in a decision support system for mammography. We show how the combination of all radiologists working with Transpara decision support software can out-perform either working individually. Finally, we discuss some of the strengths and limitations of machine learning applied to medical imaging.

Sir Michael Brady,FRS, FREng, FMedSci, Membre Étranger de l’Académie des Sciences

Emeritus Professor of Oncological Imaging, University of Oxford, GB

Founder Chairman: Perspectum Diagnostics, ScreenPoint MedicalFounder Director: Mirada Medical,Volpara Health Technologies, Chairman: Optellum

Bibb Allen Jr.,MD, FACR

Chief Medical OfficerAmerican College of RadiologyData Science InstituteDiagnostic RadiologyGrandview Medical CenterBirmingham, Alabama USA

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Wednesday, June 19, 2019 8:00 – 12:30

Salle du Choeur

8:00 21st IFCARS / SPIE / ISCAS Joint Workshop on the Digital Operating Room (DOR)Chairs: Yoshihiro Muragaki, MD (JP), Pierre Jannin, PhD (FR), Heinz U. Lemke, PhD (DE)

Smart Cyber Operating Theater (SCOT) realized through Internet of Things (IoT)Invited Speaker: Yoshihiro Muragaki, MD, PhD, Tokyo Women’s Medical University (JP)

ORNET and beyond: AI and machine learning in the OR of the futureInvited Speaker: Thomas Neumuth, PhD, ICCAS Institute (DE)

The Bonseyes-Project: democratizing Artificial Intelligence for the collaborative ORD. Ostler, N. Marahrens, D. Wilhelm, H. Feußner, Klinikum rechts der Isar of Technical Univ. of Munich (DE) [181]

GATOR: Connecting Integrated Operating Room Solutions Based on the IEEE 11073 SDC and ORiN StandardsJ. Berger, M. Rockstroh, E. Schreiber, Y. Yoshida, J. Okamoto, K. Masamune, Y. Muragaki, T. Neumuth, Univ. of Leipzig (DE); Tokyo Women’s Medical Univ.; DENSO Wave Incorporated, Aichi (JP) [19-00049]

Extending BPMN 2.0 for Intraoperative Workflow Modeling with IEEE 11073 SDC for Description and Orchestration of Interoperable, Networked Medical DevicesJ. Neumann, S. Franke, M. Rockstroh, M. Kasparick, T. Neumuth, Univ. of Leipzig; Univ. of Rostock (DE) [19-00060]

Assisted Annotation of Surgical Videos Using Deep LearningG. Lecuyer, M. Ragot, N. Martin, L. Launay, P. Jannin, IRT b<>com, Cesson-Sevigne; Univ. of Rennes 1 (FR) [19-00052]

Software assisted warning systems for endoscopic surgery – A Deep Learning based approachT. Grau, P. Schmitz, G. Strauß, KOPFZENTRUM Gruppe, Leipzig (DE) [84]

Glioma surgery in Standard Smart Cyber Operation Theater (SCOT): initial experi-ence of 5 casesY. Fujii, T. Goto, T. Ogiwara, J. Okamoto, Y. Muragaki, K. Hongo, Shinshu Univ. School of Medicine, Matsumoto; Tokyo Women’s Medical Univ. (JP) [82]

10:00 Coffee Break

10:15 4th ISCAS / CAD-AI / IFCARS Joint Symposium on Multidisciplinary Computational Anatomy (MCA)Chairs: Makoto Hashizume, MD (JP), Hiroyuki Yoshida, PhD (US)

Results of the national Japanese project on Multi-disciplinary computational anatomyInvited Speaker: Kensaku Mori, PhD, Nagoya University (JP)

Nasal airflow simulation with LDV validated LB code calculated from CBCT data sets to identify surgically relevant landmarksM. Berger, S. Schick, M. Pillei, A. Mehrle, W. Recheis, D. Dejaco, F. Kral, M. Kraxner, W. Freysinger, Management Center Innsbruck; Medical Univ. of Innsbruck; Kardinal Schwarzenberg Hosp., Schwarzach i. Pongau (AT) [59]

Statistical intensity model of lung vessels in a CT volume using β-VAEY. Saeki, A. Saito, J. Ueno, M. Harada, A. Shimizu, Tokyo Univ. of Agriculture and Technology, Koganei; Tokushima Univ. (JP) [76]

Multiple Aneurysms AnaTomy CHallenge 2019 (MATCH) – Phase II: Rupture Risk AssessmentP. Berg, S. Voß, G. Janiga, S. Saalfeld, A. W. Bergersen, K. Valen-Sendstad, J. Bruening, L. Goubergrits, A. Spuler, T. L. Chiu, A. C. O. Tsang, G. Copelli, B. Csi, Otto von Guericke Universitat Magdeburg (DE) [19-00040]

Flow-Splitting-Based Computation of Outlet Boundary Conditions for Improved Cerebrovascular Simulation in Multiple Intracranial AneurysmsS. Saalfeld, S. Voß, O. Beuing, B. Preim, P. Berg, Otto-von-Guericke-Univ. Magdeburg (DE) [19-00076]

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Wednesday, June 19, 2019 8:00 – 12:30

CARS Computer Assisted Radiology and Surgery

11:30 2nd Workshop on Digital Space Medicine (DSM)Chairs: Mario A. Cypko, PhD (NL), Krishna Kandarpa, MD, PhD (US)

Medical care and hospitalization in extreme environments like Antarctica (or space) Invited Speaker: Paul Laforet, Service médical TAAF / IPEV (French national space agency) (FR)

Space Missions Simulation Facilities and Opportunities – Developing ideas and technologiesInvited Speaker: Agata Kołodziejczyk, Analog Astronaut Training Center (PL)

Examples of Technology transfer – how to get involvedInvited Speaker: Arnaud Runge, ESTEC, European Space Agency (NL)

Human Space Flight and Space Medicine – Exploration; Change of ParadigmsInvited Speaker: Ulrich Straube, EAC, European Space Agency (DE)

12:30 Lunch Break

13:30 Special Focus Session: ERC: Europe got talentsChair: Nassir Navab, PhD (DE)

Geometric Statistics for Computational AnatomyInvited Speaker: Xavier Pennec, INRIA, Sophia-Antipolis (FR)

Molecular photoacoustic imaging during ultrasound-guided interventionsInvited Speaker: Adrien Desjardins, University College of London (GB)

COMBIOSCOPY: Computational biophotonics in endoscopyInvited Speaker: Lena Maier-Hein, DKFZ, Heidelberg (DE)

Optical theranostics: image-guided cancer thermal therapy using lightInvited Speaker: Dan Elson, Imperial College London (GB)

QuantSURG: Making Sense in Surgery using Near-Infrared Optical ImagingInvited Speaker: Sylvain Gioux, Université de Strasbourg (FR)

14:45 CMI Poster SessionSession Chairs: Christos Angelopoulos, DDS (US), Yoshihiko Hayakawa, PhD (JP)

Poster # 098 – 107

15:30 Coffee Break

16:00 Surgical NavigationSession Chairs: Akitoshi Katsumata, DDS, PhD (JP), Nermin Morgan (EG)

Future of Oral and Maxillofacial RadiologyInvited Speaker: Christos Angelopoulos, DDS, Columbia University, New York, NY (US)

3D Modeling and Virtual Reality in Oral and Maxillofacial RegionInvited Speaker: Yoshihiko Hayakawa, PhD, Kitami Institute of Technology, Hokkaido (JP)

Development of an application to evaluate the maxilla positioning after computer assisted orthognathic surgeryY. Sun, X. Hu, Y. Du, B. Vanrumste, C. Politis, Univ. Hosp. Leuven; KU Leuven (BE) [75]

Automated intraoral radiographic projection classification using convolutional neural networksN. Kyventidis, C. Angelopoulos, Aristotle Univ. of Thessaloniki (GR) [141]

Intraoperative navigation in orbit reconstructionA. Baumann, Medical Univ. of Vienna (AT) [169]

Accuracy of Low Dose Imaging Protocols of CBCT in Assessment of Peri-implant Bone DefectsN. Morgan, W. Aboelmaaty, E. Abdelfadil, M. Ashmawy, Mansoura Univ.; Ain Shams Univ., Cairo (EG) [172]

A dynamic tracking control of the robotically assisted dental implant surgical systemC. Qin, X. Chen, Z. Cao, J. Hu, Shanghai Jiao Tong Univ. (CN) [216]

17:45 End of Session


25th Computed Maxillofacial Imaging CongressChairs: Christos Angelopoulos, DDS (USA)Yoshihiko Hayakawa, PhD (JP)

Salle du Choeur

International Foundation for Computer Assisted Radiology and Surgery – IFCARSwww.ifcars.org

Medicine is undergoing a historic transition, moving away from a trial-and-error model of care, towards

individualized treatment strategies based on patient-specific knowledge management of disease and treatment. Not only the biomedi-cal systems sciences, mathematics, medical imaging and medical informatics but also the discipline of computer assisted radiol-ogy and surgery are enablers of this new

paradigm. They provide the methods and tools for knowledge management and specifically for a

patient-specific medicine.

Important aspects of these dramatically evolving methodologies and tools are:

1. Modelling of human organ systems, pathologies and clinical processes from scientific based evidence, medical guidelines and data mining.2. Analysis and adaption of models from data and information gathered from specific patients to generate knowledge models of patient-specific situations and appropriate treatment processes.3. Improved accuracy of diagnosis and optimal therapy through simulation as well as knowledge and decision management.4. Higher quality of therapy by means of real time integration of information in patient-specific models and therapeutic processes.5. Validation processes of clinical decisions on patient-specific and population levels as well as appropriate representations in repositories.

Patients, physicians and the health care systems are the beneficiaries of this development through improved quality of health care at a socially ac-ceptable cost. IFCARS with its associated CARS congress and journals are key actors in this transitional process.

The Foundation aims at supporting all measures promoting this develop-ment, in particular, the creation and communication of information in the field of computer assisted medicine and the study of its medical, social and ethical effects on our society.

The purpose of the Foundation is particularly realised by• Events of all kinds, e.g. congresses, seminars, think tank focus discussions, training and further education as well as the preparation of appropriate publications. • Support of interdisciplinary and international activities relating to the research and development of innovative public health concepts, particularly through system development and subsequent implementation and evaluation. • Promotion of national and international cooperation in science and medicine, particularly in research, development and educational activities.

Key parts of the CARS congress which address advanced methods and tools for a patient specific medicine have been initiated by IFCARS. Their inclusion in the International Journal of CARS is also promoted by IFCARS. In order to ascertain a scientific-based foundation for a modern medicine and specifically for computer assisted radiology and surgery, IFCARS is actively pursuing research and developing projects with other institutions with similar aims.

In order to accelerate the transfer of research results of CARS into clinical practice, IFCARS is also taking a leading role as an enabler of ICT sup-ported clinical trials and studies.

Finally, to increase awareness and the application of these new possibilities of a computer assisted medicine in a socially responsible way, IFCARS will establish a membership and award system to promote this historic transition of medicine.

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Thursday June 20, 2019 8:00 – 12:30

8:00 Image-guided TherapySession Chairs: Hideaki Haneishi, PhD (JP), Terry Peters, PhD (CA)

Robotic Imaging, Machine Learning and Augmented Reality for Computer Assisted InterventionsInvited Speaker: Nassir Navab, PhD, Technical Univ. of Munich (DE)

Evaluation on reconstruction accuracy of visual SLAM based bronchoscope trackingK. Mori, C. Wang, M. Oda, Y. Hayashi, T. Kitasaka, H. Itoh, H. Honma, H. Takabatake, M. Mori, H. Natori, Nagoya Univ.; Aichi Inst. of Technology, Toyota; Sapporo-Kosei General Hosp.; Sap-poro Minami-Sanjo Hosp.; Keiwakai Nishioka Hosp., Sapporo (JP) [213]

Novel Automated Vessel Pattern Characterization of Larynx Contact Endoscopic Video ImagesN. Esmaeili, A. Illanes, A. Boese, N. Davaris, C. Arens, M. Friebe, Otto-von-Guericke-Univ., Magdeburg Univ. Hosp. (DE) [19-00025]

Toward patient-specific estimation of hepatic tumors respiratory motion: A finite element-based machine learning approachM. Abayazid, H. Naghibi Beidokhti, M. Berijanian, B. Sirmaçek, Univ. of Twente, Enschede (NL) [19-00127]

Fast Image Enhancement in Optical Coherence Tomography for Retinal Disease Diagnosis and SurgeryY. Hu, J. Yang, J. Cheng, Y. Zhao, K. Masamune, J. Liu, Ningbo Inst. of Materials Technology and Engineering (CN); Tokyo Women‘s Medical Univ. (JP) [9]

9:15 Deep Learning for Image ProcessingSession Chairs: Parvin Mousavi, PhD (CA), Abed Malti, PhD, (DZ)

Convolutional neural network (CNN) applied to respiratory motion detection in fluoroscopic framesI. Vernikouskaya, C. Baldauf, A. Bäuerle, T. Ropinski, V. Rasche, Ulm Univ. Medical Center; Ulm Univ. (DE) [3]

A pilot study to classify multiple anatomical landmarks in CT by deep convolu-tional neural networkM. Nemoto, Y. Yamato, Y. Kimura, S. Hanaoka, N. Hayashi, Kindai Univ., Wakayama; The Univ. of Tokyo Hosp. (JP) [168]

Deep regression neural networks for collateral assessment from dynamic suscep-tibility contrast-enhanced magnetic resonance perfusion in acute ischemic strokeJ. T. Kwak, M. Nguyen Nhat To, H. J. Kim, H. G. Roh, Y.-S. Cho, Sejong Univ.; Konkuk Univ. Medical Center, Seoul; Catholic Univ., Deajeon (KR) [19-00034]


10:00 Poster Session 1Session Chairs: Liz Beckman, BSc (GB)

Posters # 001-018

11:30 Image Registration and its ApplicationSession Chairs: Sonia Pujol, PhD (USA), Oscar Acosta, PhD (FR)

3D registration method based on intensity gradient information for temporal subtraction technique in thoracic MDCT image N. Miyake, H. Lu, H. Kim, S. Murakami, S. Kido, T. Aoki, Kyushu Inst. of Technology; Univ. of Occupational and Environmental Health, Fukuoka; Yamaguchi Univ. (JP) [11]

Automatic registration of unordered point clouds for the study of abdominal organs and lymph node deformations.B. Villard, K. Tachi, K. Misawa, M. Oda, K. Mori, Nagoya Univ.; Aichi Cancer Center Hosp., Nagoya (JP) [19-00053]

Fusion of 3D real-time echocardiography and cine MRI using a saliency analysisA. M. Atehortúa Labrador, M. Garreau, A. Simon, E. Donal, M. Lederlin, E. Romero, Univ. of Rennes 1 (FR); National Univ. of Colombia, Bogota (CO) [19-00075]

Matching axial images of magnetic resonance imaging and transrectal ultrasound based on deep learningN. Koizumi, R. Igarashi, Y. Nishiyama, K. Tomita, Y. Shigenari, S. Shoji, The Univ. of Electro-Communications; Tokai Univ. Hachioji Hosp., Tokyo (JP) [19-00097]

12:30 Lunch Break

Room Le Réfectoire

Computer Assisted Radiology33rd International Congress and ExhibitionChairs: Ulrich Bick, MD (DE), Pierre Jannin, PhD (FR)

8:15 Surgical Robotics & InstrumentationSession Chairs: Guang-Zhong Yang, PhD (GB), Kanako Harada, PhD (JP)

Cathbot – Navigation and Control for Endovascular InterventionInvited Speaker: Guang-Zhong Yang, PhD, Imperial College London (GB)

Microsurgical robots and their evaluation using bionic humanoidsInvited Speaker: Kanako Harada, PhD, University of Tokyo (JP)

Towards Flexible Cooperative Surgical Robotics: A Review and Future ChallengesP. Schleer, S. Drobinsky, M. de la Fuente, K. Radermacher, Helmholtz Inst. for Biomedical Engineering of RWTH Aachen (DE) [18-00568]

An “eye-in-body” integrated surgery robot system for stereotactic surgeryG. Wang, L. Li, H. Ding, J. Wu, Tsinghua Univ., Beijing (CN) [19-00087]

2mm surgical manipulator with four degrees-of-freedom for transnasal endos-copy comprising elastic mechanical elementsJ. Arata, S. V. Bandara, W. Kajihara, R. Nakadate, K. Harada, M. Mitsuishi, K. Kiguchi, M. Hashizume, Kyushu Univ., Fukuoka; The Univ. of Tokyo; Kitakyushu Chuou Hosp. (JP) [209]

Portable Forceps Manipulator with Gimbal-mounted Parallel Linkage and Tel-escopic Rail Mechanism for Laparoscopic SurgeryS. Fukui, S. S. Han, T. Kawai, Y. Nishizawa, A. Nishikawa, T. Nakamura, Osaka Inst. of Tech-nology; National Cancer Center Hosp. East, Kashiwa; Shinshu Univ., Ueda; Kyoto Univ. (JP) [12]

Trans-Bronchial Biopsy Catheter Robot with Follow-The-Leader MotionN. Hata, L. Dupourquè, F. Masaki, Y. Lorig Colson, T. Kato, Brigham and Women‘s Hospital, Boston, MA (US); Ecole Polytechnique Federale de Lausanne (CH); Canon Healthcare Optics Lab, Cambridge, MA (US) [18-00612]


10:00 ISCAS Poster session 1Session Chairs: Kensaku Mori, PhD (JP), Cristian A. Linte, PhD (US)

Poster # 048 – 060

11:15 CAD-AI / ISCAS Joint Session on Artificial Intelli-gence in Computer-aided Diagnosis and Image-guided TherapySession Chairs: Hiroyuki Yoshida, PhD (US), Kensaku Mori, PhD (JP)

Artificial intelligence in CAD: clinical perspectiveInvited Speaker: Yoshiharu Ohno, MD, PhD, Fujita Health University (JP)

Polyp-size determination method using short colonoscopic video clip informationH. Itoh, Y. Mori, M. Misawa, M. Oda, S. E. Kudo, K. Mori, Nagoya Univ.; Showa Univ. Northern Yokohama Hosp. (JP) [153]

Innovation of 3D Imaging and Visualization for Intelligent Minimally Invasive SurgeryInvited Speaker: Hongen Liao, PhD, Tsinghua University, Beijing (CN)

Deep neural network for differentiation of brain tumors displayed by confocal laser endomicroscopyA. Ziebart, D. Stadniczuk, V. Roos, D. Hänggi, F. Enders, Univ. Hosp. Mannheim (DE) [103]

A multispectral snapshot camera method to analyze optical tissue characteristics in vivoE. L. Wisotzky, F. C. Uecker, P. Arens, A. Hilsmann, P. Eisert, Fraunhofer HHI; Charité Univer-sitätsmedizin, Berlin (DE) [191]

12:30 Lunch Break

23rd Annual Conference of the International Society for Computer Aided SurgeryGeneral Chairs: Kensaku Mori, PhD (JP), Cristian Linte, PhD (US)

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Thursday June 20, 2019 8:00 – 12:30

8:00 Deep Learning in Lung 1Session Chairs: Kunio Doi, PhD (US), Martin Fiebich, PhD (DE)

3D convolutional neural networks for automatic detection of lung nodules from temporal subtraction imagesY. Yoshino, H. Kim, H. Lu, S. Murakami, T. Aoki, S. Kido, Kyushu Inst. of Technology, Kitakyushu; Univ. of Occupational and Environment Health, Fukuoka; Yamaguchi Univ., Ube (JP) [74]

Preliminary study of automated detection of pulmonary nodule in ultrashort echo time MR imagesY. Nomura, S. Hanaoka, T. Yoshikawa, I. Sato, T. Nakao, M. Murata, T. Takenaga, S. Koshino, S. Miki, T. Watadani, N. Hayashi, O. Abe, The Univ. of Tokyo Hosp.; The Univ. of Tokyo Graduate School of Medicine (JP) [52]

Deep learning-based radiomics of primary lung tumors in CT images for prediction of distant metastasisJ. R. Ferreira Junior, M. Koenigkam-Santos, T. Hironaka, F. E. Garcia Cipriano, A. Todor-ovic Fabro, H. Yoshida, P. Azevedo-Marques, Univ. of São Paulo, São Carlos; Univ. of São Paulo Medical School, Ribeirão Preto (BR); Harvard Medical School, Boston, MA (US) [68]

8:45 Deep Learning in AbdomenSession Chairs: Martin Fiebich, PhD (DE), Kunio Doi, PhD (US)

Feasibility of using faster R-CNN to detect colorectal masses in high-resolution CT colonographyJ. Näppi, H. Yoshida, Massachusetts General Hosp.; Harvard Medical School, Boston, MA (US) [50]

Reduction of false-positive polyp detections in CT colonography using multiscale 3D residual networksT. Uemura, J. Näppi, H. Lu, H. Kim, R. Tachibana, T. Hironaka, H. Yoshida, Massachusetts General Hosp., Boston, MA (US); Kyushu Inst. of Technology, Fukuoka (JP) [105]

Prostate cancer detection using residual networksH. Xu, J. S. H. Baxter, O. Akin, D. Cantor-Rivera, Ezra Al Canada, Toronto, ON (CA); Memorial Sloan-Kettering Cancer Center, New York, NY (US); Univ. of Rennes 1 (FR) [19-00029]

Gastric cancer detection for gastroenterological endoscopy with local and multi-scale global informationA. Hayakawa, Y. Kurose, K. Tanaka, K. Aida, S. Satoh, M. Kitsuregawa, T. Harada, The Univ. of Toky;, Bunkyo; Kyoto Second Red Cross Hosp.; National Inst. of Informatics, Tokyo (JP) [204]

Deep learning for automatic assessment of kidney dysfunction from CT imagesJ. Pascau, M. Perera, Gonzalez-Garzon, R. San Jose Estepar, Univ. Carlos III de Madrid (ES); Brigham and Women’s Hosp., Boston, MA (US) [190]


10:00 Poster Session

Posters # 084-097

11:15 CAD-AI / ISCAS Joint Session on Artificial Intelli-gence in Computer-aided Diagnosis and Image-guidedTherapysee page 14

12:30 Lunch Break

KammermusiksaalKammermusiksaalSalle du Choeur

21st International Conference on Computer-Aided Diagnosis and Artificial Intelligence (CAD-AI)Chairman: Hiroyuki Yoshida, PhD (USA)

CARS 2019 Welcome Reception Tuesday June 18th 19:00-21:30Gallerie and Cloître

Celtic Music “Veillon-Riou” band, DJ, drinks and food.

CARS 2019 Exhibition opening receptionWednesday June 19st 18:00-20:00Exhibition space Halle 0

Visit the exhibitor, discuss with SMEs or international companies, see demos and enjoy drinks and food.

Young Investigator Networking Session / Job FairThursday June 20th 18:00-20:00Exhibition space Halle 0

At the YINS Job Fair, you can find a job or collaborators or just relax with DJ, bar, drinks and finger food.

Free guided tour of the historical city of RennesThursday June 22nd 19:15-20:45Free registration at www.cars2019.org. Limited tickets available.

Explore Rennes, the capital of Brittany, from a new perspective with this guided tour of the city centre, spanning centuries of history. Discover Rennes' medieval character with its colourful half-timbered houses and imposing defensive gates, the Portes Mordelaises. Watch it give way to the ornate gothic architecture of Saint-Yves Chapel. Be transported to the era of Louis XV and pre-Revolution France with Rennes' city hall and marvel at the Parliament of Brittany and the remarkable private mansions built for those “men of the Parliament.”

CARS 2019 Farewell partyFriday June 21st 18:00-21:00Rooms Gallerie and Cloitre

Let’s celebrate CARS 2019 and La Fête de la Musique (World Music Day) with DJ, drinks and finger food.

Tour: From Mont Saint-Michel to Saint-Malo …Saturday June 22nd 8:30-18:30Separate registration at www.cars2019.org. Limited seats available.

Along the coast of the English Channel lies the historic abbey of Mont Saint-Michel, perched on a rock in a bay regularly invaded by swirling high tides. This tidal island's winding streets, abbeys, and defensive walls bear witness to thirteen centuries of history. Further along the coast lies the fortified city of Saint-Malo, once dubbed the “Corsair City” due to itsnefarious association with piracy. Come visit this historical city centre, admire its imposing Grand Bé and Petit Bé island fortresses, and walk in the footsteps of famous seafarers such as Jacques Cartier and Samuel de Champlain. 90€ including– A professional local guide for the visits– Entrance ticket to the Mont Saint-Michel abbey– Three course lunch menu with wine and coffee– Guided tour of Saint-Malo– Transport in a comfortable coach bus

CARS 2019 Social Events

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Thursday, June 20, 2019 13:30 – 19:00 Thursday, June 20, 2019 13:30 – 19:00

13:30 Mixed reality for Surgical Simulation, Training and EducationSession Chairs: Carla Pugh, MD, PhD (US), Roy Eagleson, PhD (CA)

Use of Sensor-Based Metrics to Improve Mastery Learning During SimulationInvited Speaker: Carla Pugh, MD, PhD, Stanford University (US)

Orthopaedics residents basics skills learning with virtual reality arthroscopy simulator: a large national prospective studyP. Walbron, H. Thomazeau, H. Common, E. Bernard, F. Sirveaux, Univ. Hosp. of Nancy; Univ. Hosp. of Rennes (FR) [225]

An AR-Solution for Education and Consultation during Microscopic SurgeryA. Schneider, M. Lanski, M. Bauer, E. Wisotzky, J. C. Rosenthal, ARRI Medical GmbH; pripares GmbH, Munich; Fraunhofer Heinrich Hertz Inst., Berlin (DE) [178]

Anxiety Reduction System for Glioma Patients undergoing Awake Surgery using Virtual RealityY. Horise, Y. Kasuya, K. Takada, T. Onishi, A. Takahashi, T. Taipaleenmaki, H. Iseki, K. Masamune, Y. Muragaki, Tokyo Women‘s Medical Univ.; NTT docomo Inc.; Nokia Solutions and Networks Japan; Waseda Univ., Tokyo (JP) [218]

An augmented reality guidance system for endovascular aortic repair: first steps in reducing radiation exposureF. von Haxthausen, S. Jäckle, J. Bouchagiar, F. Matysiak, M. Kaschwich, J.-P. Goltz, E. Stahlberg, M. Kleemann, F. Ernst, V. García-Vázquez, Univ. of Lübeck; Univ. Hosp. Schleswig-Holstein, Lübeck; Fraunhofer MEVIS, Lübeck (DE) [19-00028]

14:45 ISCAS General Assembly15:30 Coffee Break

16:00 Computational Methods for Image-guided TherapySession Chairs: Parvin Mousavi, PhD (CA), Simon Drouin, PhD (CA)

Source-detector trajectory optimization for C-arm CBCTS. Hatamikia, A. Biguri, G. Kronreif, H. Furtado, J. Kettenbach, M. Figl, W. Birkfellner, Austrian Center for Med. Innovation and Technology, Vienna; Medical Univ. of Vienna; Landesklinikum Wiener Neustadt (AT); Univ. of Southampton (GB) [23]

Automatic segmentation of attention-aware artery region in laparoscopic colorec-tal surgeryH. Itoh, S. Morimitsu, T. Ozawa, H. Oda, T. Kitasaka, T. Sugino, Y. Hayashi, N. Takeshita, M. Ito, M. Oda, K. Mori, Nagoya Univ.; Aichi Inst. of Technology, Toyota; National Cancer Center Hosp. East, Kashiwa (JP) [107]

Stereotactic Image-Guided Microwave Ablation for malignant liver tumors – Can computer-assistance broaden treatment eligibility?P. Tinguely, L. Frehner, A. Lachenmayer, V. Banz, S. Weber, D. Candinas, M. Maurer, Inselspi-tal Univ. of Bern; Univ. of Bern (CH) [182]

Gabor-domain optical coherence microscopy for optical biopsy, image-guided surgery, and intraoperative imagingC. Canavesi, R. O‘Connell, T. Paczos, A. Cogliati, A. Hayes, A. Bonham, J. Rolland, LighT-opTech Corp., West Henrietta, NY; Univ. of Rochester Medical Center, NY (US) [185]

Accounting for surgical aerosol propagation delay in navigated intra-operative tissue characterization by mass spectrometryM. Asselin, J. Wiercigroch, K. Sunderland, M. Kaufmann, N. Janssen, T. Ungi, A. Lasso, J. Rudan, G. Fichtinger, Queen‘s Univ., Kingston, ON (CA) [161]

Utilizing a convolutional neural network for tool detection in central venous catheterizationT. Ungi, J. Isen, R. Hisey, G. Fichtinger, Laboratory for Percutaneous Surgery, Kingston, ON (CA) [201]

Real-time surgical needle detection using region-based convolutional neural networksA. Nakazawa, K. Harada, M. Mitsuishi, P. Jannin, The Univ. of Tokyo (JP); Univ. of Rennes 1 (FR) [19-00066]

13:45 Image Segmentation by Machine Learning (1)Session Chairs: Florent Lalys, PhD (FR), François Rousseau, PhD (FR)

DeepFlow: Integrating Conditional Random Fields and Deep LearningInvited Speaker: John Baxter, PhD, University of Rennes (FR)

Evaluation of squeeze and excitation fully convolutional networks for multi-organ segmentationC. Shen, F. Milletari, H. Roth, M. Oda, B. Villard, Y. Hayashi, K. Misawa, K. Mori, Nagoya Univ.; Aichi Cancer Center Hosp., Nagoya (JP); NIVIDIA, Santa Clara, CA (US) [146]

Segmentation of Organs at Risk in Head and Neck Radiation Therapy with 3D Convolutional Networks M. Concepción-Brito, R. Moreta-Martinez, J. Serrano, D. García-Mato, M. García-Sevilla, J. Pascau, Inst. de Investigación Sanitaria Gregorio Marañón, Madrid (ES) [166]

14:30 Image Segmentation by Machine Learning (2)Session Chairs: Purang Abolmaesumi, PhD (CA), John Baxter, PhD (FR)

MultiAtlas Neonatal Brain MRI Segmentation: From Patch-based to Deep ApproachesInvited Speaker: François Rousseau, PhD, LaTIM U1101 INSERM, Brest (FR)

A comparison of conventional and deep learning methods of image segmentation on aortic dissectionC. Shao, T. Lv, J. Tomasi, X. Zhao, J. P. Verhoye, G. Yang, Y. Chen, P. Haigron, Ansys, Villeurbane; Univ. of Rennes 1 (FR); Southeast Univ., Nanjing (CN) [96]

Liver Tissue Segmentation In Multiphase CT Scans Using Cascaded Convolutional Neural NetworksF. Ouhmich, V. Agnus, V. Noblet, F. Heitz, P. Pessaux, Nouvel Hopital Civil, Strasbourg; Univ. of Strasbourg, Illkirch (FR) [19-00090]

Cerebrovasculature segmentation via FCNN for SEEG trajectory planningS. El Hadji, S. Moccia, D. Scorza, F. Cardinale, G. Baselli, E. De Momi, Politecnico di Milano; Niguarda Hosp. Ca’ Granda, Milan; Univ. Politecnica delle Marche, Ancona (IT) [19-00105]

15:30 Coffee Break

16:00 Image Segmentation: Other Innovative ApproachesSession Chairs: D. Louis Collins, PhD (CA), Su Ruan, PhD (FR)

MD+Machine: Machine Learning for Computer Aided Diagnosis and Interventions in Prostate CancerInvited Speaker: Parvin Mousavi, PhD, Queens University, Kingston, Ontario (CA)

Automated Segmentation of Oriented Branching Structures through Dilation Shells using Dynamic ProgramingG. Stetten, M. Wu, L. Wang, H. Aizenstein, Univ. of Pittsburgh; Univ. of Pittsburgh Medical Center, PA (US) [19-00021]

User-dependent variability in mitral valve segmentation and its impact on CFD computed hemodynamic parametersK. Vellguth, J. Brüning, L. Tautz, S. Sündermann, F. Degener, I. Wamala, V. Falk, U. Kertzscher, A. Hennemuth, T. Kühne, L. Goubergrits, Charité – Universitätsmedizin Berlin; German Heart Inst. Berlin (DE) [19-00069]

Capsule Networks for Mother‘s Womb Segmentation in TTTS Fetal Surgery PlanningM. Ceresa, J. Torrents-Barrena, R. López-Velazco, G. Piella, E. Gratacós, E. Eixarch, M. A. González Ballester, Univ. Pompeu Fabra, Barcelona; Univ. of Barcelona (ES) [121]

Segmentation-based registration of ultrasound volumesL. Canalini, J. Klein, D. Miller, R. Kikinis, Fraunhofer MEVIS, Bremen; Universitätsklinikum Knappschaftskrankenhaus Bochum (DE) [19-00030]

Automatic detection of morphological structures in Intravascular Ultrasound im-ages whit Convolutional Neural NetworkE. Moris, L. D. Lo Vercio, I. Larrabide, Univ. Nacional del Centro de la Provincia de Buenos Aires, Tandil (AR) [19-00064]

17:30 Exhibition Tour

18:00 YINS and Job Fair

8:00 CAR / CAD-AI Joint Session on Deep Learning and

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13:30 Deep Learning in Lung 2Session Chairs: Paulo M. Azevedo-Marques, PhD (BR), Shoji Kido, MD, PhD (JP)

Detecting lung lesions based on deep learning for constructing medically-mean-ingful TB descriptorsV. Kovalev, V. Liauchuk, A. Tarasau, E. Snezhko, A. Gabrielian, A. Rosenthal, United Inst. of Informatics Problems; Scientific and Practical Center for Pulmonology and Tuberculo-sis, Minsk (BY); National Inst. of Allergy and Infectional Diseases, Bethesda, MD (US) [95]

Convolutional neural network for 3D CADv systems: Utility for differentiation of malignant from benign pulmonary nodulesY. Ohno, A. Yaguchi, K. Aoyagi, Y. Kishida, S. Seki, Y. Ueno, T. Yoshikawa, Kobe Univ. Graduate School of Medicine (JP) [16]

Improving lung cancer prediction with a deep learning nodule malignancy classifierX. Rafael-Palou, I. Bonavita, M. Ceresa, G. Piella, V. Ribas-Ripoll, M. A. González Bal-lester, Eurecat; Univ. Pompeu Fabra, Barcelona (ES) [73]

Lung nodule classification using deep local-global networksM. Tan, M. Al Shabi, B. L. Lan, W. Y. Chan, K.-H. Ng, Monash Univ., Subang Jaya (MY); Univ. of Oklahoma, Norman, OK (US) [19-00018]

14:30 Radiomics 1Session Chair: Akinobu Shimizu, PhD (JP), Janne J. Näppi, PhD (US)

Machine learning based lung cancer diagnosis using post-contrast T1-weighted and T2-weighted magnetic resonance imaging.P. Azevedo-Marques, V. Francisco, D. Wada, J. R. Ferreira Junior, A. Fabro, F. Cipriano, L. Ferreira, S. Quatrina, M. Koenigkam-Santos, Univ. of São Paulo, São Carlos; Univ. of São Paulo Medical School, Ribeirão Preto (BR) [47]

A radiomics approach for differentiation of pseudocavitation from cavitation on lung cancer tumorsP. Azevedo-Marques, J. R. Ferreira Junior, M. Koenigkam-Santos, Y. Kikuchi, M. Faleiros, F. E. Garcia Cipriano, A. Todorovic Fabro, H. Yoshida, Univ. of São Paulo, São Carlos; Univ. of São Paulo Medical School, Ribeirão Preto (BR); Harvard Medical School, Boston, MA (US) [69]

Identifying alterations in the cardiac ventricles in atrial fibrillation: a radiomics approachI. Cetin, S. E. Petersen, O. Camara, M. A. Gonzalez Ballester, K. Lekadir, Univ. Pompeu Fabra, Barcelona (ES); Queen Mary Univ. of London (GB) [94]

Tissue classification of esophagus resected tissue based on hyperspectral dataM. Maktabi, H. Köhler, M. Ivanova, J. Takoh, S. Rabe, B. Jansen-Winkeln, S. Niebisch, I. Gockel, C. Chalopin, Univ. of Leipzig; Univ. Hosp. Leipzig (DE) [19-00071]

16:00 Radiomics 2Session Chair: Ruey-Feng Chang, PhD (TW), Yoshiharu Ohno, MD, PhD (JP)

Artificial neural network for the prediction of colorectal lymph node metastasisB. Villard, H. Itoh, K. Ichimasa, Y. Mori, M. Misawa, M. Oda, S. Kudo, K. Mori, Nagoya Univ.; Showa Univ. Northern Yokohama Hosp. (JP) [19-00102]

A novel method of determining breast cancer risk using parenchymal textural analysis of mammography imagesM. Tan, S. Mariapun, C. H. Yip, K. H. Ng, S. H. Teo, Monash Univ. Malaysia; Subang Jaya Medical Centre, Selangor; Univ. of Malaya, Kuala Lumpur (MY) [77]

16:30 Deep Learning in Breast, Eye, Brain, MusculoskeletalSession Chairs: Hiroshi Fujita, PhD (JP), Ruey-Feng Chang, PhD (TW)

Tumor detection for automated breast ultrasound using 3-D convolutional neural networkR. F. Chang, Y. S. Huang, C. H. Hsu, National Taiwan Univ., Taipei (TW) [21]

Classification of breast cancer histology images using consensus oriented by three deep convolutional neural networksI. Nedjar, S. Mahmoudi, M. A. Chikh, Tlemcen Univ. (DZ); Univ. of Mons (BE) [192]

Optical coherence tomography classification of multiple retinal diseases using DenseNetK. Mori, C. Wang, M. Oda, Y. Itoh, Nagoya Univ.; Nagoya Univ. Graduate School of Medicine (JP) [120]

Retinal OCT disease classification with variational autoencoder regularizationM. H. Laves, S. Ihler, L. A. Kahrs, T. Ortmaier, Leibniz Univ. Hannover (DE) [222]

3D deep convolutional neural network using SPECT images for classification of dementia typeM. Yambe, A. Saito, M. Fukasawa, T. Iizuka, A. Shimizu, Tokyo Univ. of Agriculture and Technology, Koganei; Fukujuji Hosp., Kiyose (JP) [60]

Detection of hip fractures on digital pelvic radiographs using a deep convolution neural networkT. Mawatari, R. Murakami, S. Katsuragawa, Y. Hayashida, Teikyo Univ., Omuta; Univ. of Occupational and Environmental Health School of Medicine, Kitakyushu (JP) [41]


Room La Nef Salle du Choeur

21st International Conference on Computer-Aided Diagnosis and Artificial Intelligence (CAD-AI)Chairman: Hiroyuki Yoshida, PhD (USA)

Room Le Réfectoire


June 23–26, 2020Munich, Germany

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COMPUTER ASSISTED RADIOLOGY AND SURGERY

CARS 2020

34th International Congress and Exhibition

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Friday, June 21, 2019 8:00 – 12:30 Friday, June 21, 2019 13:30 – 18:00

8:15 Image-guided Neuro-interventions and ApplicationsSession Chairs: Sandrine de Ribaupierre, MD (CA), Thomas Lango, PhD (NO)

Endoscopic endonasal approach in Smart Cyber Operation Theater (SCOT): prelim-inary clinical applicationT. Ogiwara, A. Nagm, T. Goto, Y. Fujii, T. Nakamura, K. Hongo, J. Okamoto, Y. Muragaki, Shinshu Univ. School of Medicine, Matsumoto; Tokyo Women‘s Medical Univ. (JP) [64]

Structured Light Scanning for Morphometric Analysis in Craniosynostosis Recon-struction SurgeryD. García-Mato, M. García-Sevilla, S. Ochandiano, C. Navarro-Cuéllar, J. V. Darriba-Allés, R. García-Leal, J. Pascau, Univ. Carlos III de Madrid; Hosp. General Universitario Gregorio Marañón, Madrid (ES) [183]

Projection-mapping navigation with image deformation tracking for brain surgeriesY. Nakajima, Y. Sohma, J. Jiang, Tokyo Medical and Dental Univ.; The Univ. of Tokyo (JP) [214]

The development of non-contact user interface of a surgical navigation system based on Kinect depth camera and a phantom experiment for zygomatic implant placementC. Qin, X. Chen, X. Ran, Y. Wu, Shanghai Jiao Tong Univ.; Zhejiang Univ. (CN) [19-00047]

9:15 Rapid Prototyping Applications in Image-guided TherapySession Chairs: Marta Kersten-Oertel, PhD (CA), Ichiro Sakuma, PhD (JP)

Rapid prototyping framework for image-guided interventionsI. Vernikouskaya, D. Bertsche, W. Rottbauer, V. Rasche, Ulm Univ. Medical Center (DE) [45]

Optimizing navigation with patient-specific 3D printed guides in pelvic tumor resection surgeryD. García-Mato, M. García-Sevilla, J. Calvo-Haro, R. Pérez-Mañanes, J. Pascau, Univ. Carlos III de Madrid; General Univ. Hosp. Gregorio Maranon, Madrid (ES) [176]

Accuracy of Mastoid Surface Templates for Targeting Temporal Bone AnatomyW. Morrel, R. Labadie, J. Noble, Vanderbilt Univ. Medical Center; Vanderbilt Univ., Nashville, TN (US) [188]


10:30 ISCAS Poster session 2Session Chairs: Kensaku Mori, PhD (JP), Cristian A. Linte, PhD (US)

Poster # 061 – 83

11:15 Workflow Analysis and Modeling for Image-guided TherapySession Chairs: Cristian A. Linte, PhD (US), Caroline Essert, PhD (FR)

Predicting the quality of surgical exposure using spatial and procedural features from laparoscopic videosA. Derathé, F. Reche, A. Moreau-Gaudry, P. Jannin, B. Gibaud, S. Voros, Univ. Grenoble Alpes, La Tronche; Univ. of Rennes 1 (FR) [19-00131]

Recognizing surgical actions of Robot-Assisted Partial NephrectomyH. C. Nakawala, L. E. Pescatori, R. Bianchi, O. De Cobelli, G. Ferrigno, P. Fiorini, E. De Momi, Univ. of Verona; Polytechnico di Milano; European Inst. of Oncology, Milan (IT) [19-00104]

Automatic annotation of surgical activities using virtual-reality environmentsA. Huaulmé, F. Despinoy, S. A. Heredia Perez, K. Harada, M. Mitshuishi, P. Jannin, Univ. of Rennes 1 (FR); The Univ. of Tokyo (JP) [19-00056]

Cognitive Load Associations when utilizing Auditory Display within Image-Guided NeurosurgeryM. Kersten-Oertel, J. Plazak, D. di Giovanni, D. L. Collins, Concordia Univ.; McGill Univ., Montreal, QC (CA) [19-00050]

12:30 Lunch Break

GAN in Medical ImagingSession Chairs: Hiroyuki Yoshida, PhD (US), Pierre Jannin, PhD (FR)

The Challenge for AI in Medical Imaging in ChinaInvited Speaker: Huimao Zhang, MD, PhD, The First Hospital of Jilin University, Changchun City (CN)

Recent progress in Medical Image Processing and Deep LearningInvited Speaker: D. Louis Collins, PhD, McGill University, Montreal, Quebec (CA)

Enhancing virtual bronchoscopy with intra-operative data using multi-objective GANsD. Gil, A. Esteban, C. Sánchez, A. Borras, Autonomous Univ. of Barcelona (ES) [20]

Weakly-supervised Generative Adversarial Networks for Deformable Image RegistrationZ. Li, M. Ogino, Hitachi, Ltd., Tokyo (JP) [115]

CycleGAN for style transfer in x-ray angiographyO. Tmenova, R. Martin, L. Duong, École de technologie supérieure, Montréal, QC (CA) [19-00031]

Synthesis of CT Images from Digital Body Phantoms Using CycleGANsT. Russ, S. Goerttler, A.-K. Schnurr, D. F. Bauer, L. R. Schad, F. G. Zöllner, K. Chung, Univ. of Heidelberg, Mannheim (DE) [19-00120]

Generative adversarial learning-based electronic cleansing system for CT colonographyR. Tachibana, J. J. Näppi, T. Hironaka, H. Yoshida, National Inst. of Technology, Oshima (JP); Massachusetts General Hosp., Boston, MA (US) [129]

Generative adversarial learning-based prediction of survival of patients with interstitial lung diseasesT. Uemura, C. Watari, J. Nappi, T. Hironaka, H. Yoshida, Massachusetts General Hospital / Harvard Medical School, Boston, MA (US) [37]


10:30 Poster Session 2Session Chairs: Gabriele von Voigt, PhD (DE)

Posters # 019-047

11:30 Visualization and Augmented RealitySession Chairs: Marta Kersten-Oertel, PhD (CA), Ulrich Eck, PhD (DE)

Spatial augmented reality system with real-time methods for soft tissue deforma-tion compensationS. Ilango, L. A. Kahrs, T. Ortmaier, Leibniz Univ. Hannover (DE) [142]

Introducing a zoom-independent calibration target for augmented reality applica-tions using a digital surgical microscopeJ. C. Rosenthal, A. Schneider, P. Eisert, Fraunhofer Inst. for Telecommunications, Berlin; ARRI Medical GmbH, Munich (DE) [187]

Considering visibility of vascular virtual handling system for endovascular inter-vention assistanceT. Shinohara, Y. Nishida, N. Nakasako, Kindai Univ., Kinokawa (JP) [14]

A Web-based collaborative Multidisciplinary Team Meeting Visualisation SystemH. Jung, Y. Jung, D. D. Feng, M. Fulham, J. Kim, Univ. of Sydney, NSW (AU) [19-00093]

12:30 Lunch Break

13:30 Image Analysis (1)


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Room Le Réfectoire

13:30 Interventional Robotics for OrthopedicsSession Chairs: Kevin Cleary, PhD (US), Tamas Ungi, PhD (CA)

New Horizons in orthopedic surgery: Past, present and future perspectivesInvited Speaker: Pedro Alvarez Diaz, MD, PhD, International University of Catalunya, Barcelona (ES)

PedBotHome: robotically-assisted ankle rehabilitation system for home use for children with cerebral palsyS.H. Evans, R. Monfaredi, T. Salvador, H. F. Talari, C. Coley, S. Kovelman, J. Belschner, S. Alyamani, K. Cleary, Children‘s National, Washington, DC (US) [71]

Early Experience with Force-Space Navigated Robotics for Glenoid Implantation during Total Shoulder ArthroplastyC. Smith, G. Athwal, L. Ferriera, Western Univ.; St. Joseph‘s Health Care, London, ON (CA) [173]

A comparative analysis of intensity-based 2D-3D registration for intraoperative use in pedicle screw insertion surgeriesH. Esfandiari, C. Anglin, P. Guy, J. Street, A. J. Hodgson, Univ. of British Columbia, Vancouver, BC; Univ. of Calgary, AL (CA) [19-00011]

14:30 Image-guided Orthopedic InterventionsSession Chairs: Amber Simpson, PhD (US), Pedro Alvarez Diaz, MD, PhD (ES)

3D reconstruction of the knee bone surface using markerless 3D ultrasoundM. Nasan, Y. Morvan, G. Dardenne, J. Chaoui, E. Stindel, LaTIM, Brest; Wright Medical Group, Inc., Plouzané (FR) [156]

Electromagnetically Navigated Forearm Fracture PlatingD.R. Pichora, P. Lin, J. Chan, R.E. Ellis, Queen‘s Univ., Kingston, ON (CA) [51]

Knee Arthroscopic Navigation using Virtual-vision Rendering and Self-positioning TechnologyH. Liao, C. Ma, X. Cui, F. Chen, L. Ma, S. Xin, Tsinghua Univ. School of Medicine, Beijing; Nanjing Univ. of Aeronautics and Astronautics (CN) [19-00098]

15:30 Coffee Break

16:00 Motion & Shape Tracking and Analysis for Image-guided TherapySession Chairs: Elvis C.S. Chen, PhD (CA), Gabor Fichtinger, PhD (CA)

Combining Position-Based Dynamics and Gradient Vector Flow for Mitral Valve Tracking in TEE UltrasoundL. Tautz, L. Walczak, J. Georgii, S. Sündermann, V. Falk, A. Hennemuth, Fraunhofer MEVIS, Bremen; Charité Universitätsmedizin Berlin (DE) [19-00083]

Surface Deformation Analysis of Deaerated Lungs using Model-based Shape MatchingM. Nakao, J. Tokuno, T. Chen-Yoshikawa, H. Date, T. Matsuda, Kyoto Univ.; Kyoto Univ. Hosp. (JP) [19-00114]

Respiratory motion prediction and tumor tracking with electromagnetic and optical tracking technology Z. Bardosi, Y. Özbek, W. Freysinger, Medical Univ. of Innsbruck (AT) [38]

Fine-Tuning Neural Networks for Fast and Robust Optical Flow Estimation in Endoscopic SurgeryS. Ihler, J. P. Schulz, L. A. Kahrs, T. Ortmaier, Leibniz Univ. Hannover (DE) [19-00133]

Forceps Motion Analysis from Endoscope Videos using Deep Learning for Quantitative Evaluation of Endoscopic Sinus Surgery TrainingA. Matsui, N. Ootori, K. Ohmura, R. Nakamura, Chiba Univ.; Jikei Univ. School of Medicine, Tokyo (JP) [108]

17:15 ISCAS Award CeremonyChairs: Kensaku Mori, PhD (JP), Cristian A. Linte, PhD (US)

Session Chairs: Miguel Á. González Ballester, PhD (ES), Yoshikazu Nakajima, PhD (JP)

Generation of three-dimensional myocardial blood flow distribution by image reconstruction of coronary angiographic imagesT. Kato, T. Ohnishi, K. Nakano, T. Kasahara, K. Miura, H. Kitahara, H. Haneishi, Chiba Univ.; Chiba Univ. Hosp. (JP) [54]

A new method for reducing large motion artifacts of DSA based on deep learning techniqueM. Yamamoto, Y. Okura, H. Kawata, N. Yamamoto, Hiroshima International Univ.; Kurume Univ. Hosp., Fukuoka (JP) [114]

Computer simulation of low-dose chest radiographs from a real high-dose radiographR. Murakami, T. Mawatari, S. Katsuragawa, Teikyo Univ., Omuta (JP) [43]

Computer-based virtual clinical trial for pulmonary function diagnosis with dynamic chest radiographR. Tanaka, E. Samei, W. P. Segars, E. Abadi, H. Roth, H. Oda, K. Mori, Kanazawa Univ.; Nagoya Univ. (JP); Duke Univ., Durham, NC (US) [53]

14:30 Image Analysis (2)Session Chairs: Gabriele von Voigt, PhD (DE), Xiongbiao Luo, PhD (CN)

Detection and Segmentation of Lymphomas in 3D PET Images via Clustering with Entropy-based Optimization StrategyS. Ruan, H. Hu, P. Decazes, P. Vera, H. Li, Univ. of Rouen Normandie; Centre Henri Becquerel Hosp., Rouen (FR); Washington Univ., St. Louis, MO (US) [19-00007]

A closer look onto breast density with weakly supervised dense-tissue masksM. Tardy, B. Scheffer, D. Mateus, Ecole Centrale de Nantes; Integrated Center for Oncology, Saint-Herblain (FR) [19-00079-P]

A Deep Learning Framework For Efficient Analysis Of Breast Volume and Fibrog-landular Tissue Using MR Data With Strong ArtifactsT. Ivanovska, T. G. Jentschke, A. Daboul, K. Hegenscheid, H. Völzke, F. Wörgötter, Georg-August-Univ. Göttingen; Universitätsmedizin Greifswald (DE) [18-00554]

Multi-planar pose prediction in medical imagingB. Maris, E. Ghignoni, P. Fiorini, Univ. of Verona (IT) [122]

15:30 Coffee Break

16:00 Decision Support, PredictionSession Chairs: Amber Simpson, PhD (US), Liz Beckman, BSc (GB)

Ultrafast imaging and Superresolution Ultrasound for MedicineInvited Speaker: Mickael Tanter, PhD, INSERM ESPCI Paris (FR)

Position-based modeling of lesion displacement in Ultrasound guided breast biopsyE. Tagliabue, D. Dall’Alba, E. Magnabosco, C. Tenga, P. Fiorini, Univ. of Verona (IT) [19-00039]

Can one predict brain disease based on cardiac imaging data? A proof-of-concept studyM. Masias Bruns, I. Cetin, S. E. Petersen, M. A. Gonzalez Ballester, G. Piella, K. Lekadir, Univ. Pompeu Fabra, Barcelona (ES); Queen Mary Univ. of London (GB) [97]

Validation of the larynx cancer model regarding treatment decisionM. Stoehr, A. Hikal, A. Oeser, M. A. Cypko, H. U. Lemke, A. Dietz, Univ. of Leipzig (DE) [171]

Morphology-based estimation of disease duration in multiple sclerosis patients using T1-weighted MRI datasetsN. Subbanna, A. Rauscher, D. Li, A. Traboulsee, B. Pike, N. Forkert, Univ. of Calgary, AL; Univ. of British Columbia, Vancouver, BC (CA) [196]

Comparison of statistical learning approaches for cerebral aneurysm rupture assessmentF. J. Detmer, D. Lückehe, F. Mut, M. Slawski, S. Hirsch, P. Bijlenga, G. von Voigt, J. R. Cebral, George Mason Univ., Fairfax, VA (US); Leibniz Univ. Hannover (DE); Univ. of Geneva; Zurich Univ. of Applied Sciences, Wädenswil (CH) [19-00118]

17:30 CARS Closing CeremonyChairs: Pierre Jannin, PhD (FR), Kensaku Mori, PhD (JP), Hiroyuki Yoshida, PhD (US), Heinz U. Lemke, PhD (DE)

18:00 CARS 2019 Farewell Party


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Poster Presentation TimesA poster author or coauthor is required to stand by the poster during the scheduled poster sessions to answer questions from attendees. Schedules depend on the conference track (see poster list).

Presenters who have not placed their poster(s) on their as-signed board by 30 minutes prior to the session on the day of their presentation will be considered a “no show”.

CAR/CARS

001 – 018 019 – 048

Thursday, June 20Friday, June 20

10:00 – 11:15 10:00 – 11:15

ISCAS 048 – 060 061 – 083

Thursday, June 20Friday, June 20

10:00 – 11:15 10:00 – 11:15

IPCAI Tuesday, June 18

Wednesday, June 19

12:00 – 13:3015:30 – 17:0012:30 – 13:3015:30 – 17:30

CAD-AI 88 – 96 Thursday, June 20 10:00 – 11:15CMI Interactive Poster SessionAuthors will present main findings of their paper in a 5’ presentation in the corresponding CMI interactive session 97 – 107 Wednesday, June 19 14:45 – 15:40

CAR / CARS

001 Image quality of low tube voltage on 2nd genera-tion dual-source CT angiography for partial nephrec-tomy 3D simulation: a phantom studyK. Ohashi, A. Okada, Y. Hirose, T. Yasui, Y. Shibamoto, Nagoya City Univ. Hosp.; Nagoya City Univ. Graduate School of Medical Sciences (JP) [7]

002 Non-contrast to contrasted abdominal CT volume regression using fully convolutional networkM. Oda, K. K. Kumamaru, S. Aoki, K. Mori, Nagoya Univ.; Juntendo Univ.,Tokyo (JP) [29]

003 Anatomical keypoints localization in 3D CT scans using regression CNNF. Lalys, H. Hammami, A. Landreau, Therenva SAS, Rennes (FR) [30]

004 Deep learning-based dual-energy computed tomography imagingY. Chen, T. Lv, W. Zhao, Q. Zhao, L. Xing, Southeast Univ., Nanjing (CN); Stanford Univ., CA (US) [83]

005 70 kVp CT angiography for preoperative assess-ment of robot assisted partial nephrectomy (RAPN): comparison with 120 kVp imagingW. Tani, N. Negi, Kobe Univ. Hosp. (JP) [88]

006 Image noise characteristic of deep learning-based reconstruction image in precision detector computed tomographyA. Urikura, Y. Nakaya, T. Yoshida, T. Hara, E. Nishimaru, M. Endo, Shizuoka Cancer Centre; Nakatsugawa Municipal General Hosp., Gifu; Hiroshima Univ. Hosp. (JP) [130]

007 Artifacts reduction for analyzing postmortem CT images by using deep learningS. Chai, Y. Hirano, S. Kido, K. Kinoshita, K. Inai, S. Noriki, Yamaguchi Univ., Ube; Univ. of Fukui, Eiheiji (JP) [155]

008 Analysis of colon curvatures in CT colonography images in different patient positionsG. Fichtinger, J. Laframboise, K. Barr, P. Tan, L. Hookey, T. Ungi, Queen’s Univ., Kingston, ON (CA) [199]

009 Reference misalignment detection and correction for atrial fibrillation catheter ablationA. J. Stewart, S. Sebastyan, M. Kunz, D. Redfearn, Queen’s Univ., Kingston, ON (CA) [207]

010 Clinical Information Analyzer system to support surgery toward realization of AI surgeryK. Kusuda, J. Okamoto, Y. Horise, M. Tamura, E. Kobayashi, Y. Muragaki, K. Masamune, Tokyo Women’s Medical Univ. (JP) [211]

011 Bone suppression for chest X-ray image using a convolutional neural filterN. Matsubara, A. Teramoto, K. Saito, H. Fujita, Fujita Health Univ., Toyoake; Gifu Univ. (JP) [19-00046]

012 Dynamic contrast-enhanced CT diagnosis of primary liver cancers using transfer learning of pre-trained convolutional neural network: Is manual registration of multi-phasic images by radiologists needed?A. Yamada, K. Oyama, S. Fujita, E. Yoshizawa, F. Ichinohe, D. Komatsu, Y. Fujinaga, Shinshu Univ. School of Medicine, Nagano (JP) [19-00055]

013 Online calibration of a mobile C-arm using inertial sensors: a feasibility study in order to achieve CBCTI. Lemammer, O. Michel, H. Ayasso, S. Zozor, G. Bernard, Univ. Grenoble Alpes; Thales AVS France, Moirans (FR) [19-00062]

014 Improving realism in patient-specific abdominal Ultrasound simulation using CycleGANsS. Vitale, J. I. Orlando, E. Iarussi, I. Larrabide, Univ. Nacional del Centro de la Provincia de Buenos Aires, Tandil (AR); Medical Univ. of Vienna (AT) [19-00078]

015 Deep Learning-based Digital Subtraction Angiog-raphy Image GenerationY. Chen, Y. Song, X. Yin, W. Wu, W. Shi, Southeast Univ., Nanjing; Nanjing Medical Univ.; Chongqing Univ. (CN) [19-00088]

016 Downsampled Cerebral CT Perfusion Image Restoration with CNNH. Zhu, Y. Chen, S. Wang, W. Wu, H. Tang, L. Luo, South-east Univ., Nanjing; Chongqing Univ. (CN) [19-00096]

017 Markerless pose estimation of a endoscope-com-patible fiberprobe for optical biopsy : a feasibility studyO. Zenteno, S. Treuillet, Y. Lucas, Univ. of Orleans (FR) [19-00107]

018 Mesh Optimization and Centerline Extraction of vasculature for Endovascular Intervention SimulationW. Si, D. Zhu, H. Xie, M. Wei, W. S. Ho, F. L. Wang, J. Qin, Shenzhen Inst. of Advanced Technology; Nanjing Univ. of Aeronautics and Astronautic (CN); The Hong Kong Polytechnic Univ.; The Education Univ. of Hong Kong; The Open Univ. of Hong Kong; Caritas Inst. of Higher Education (HK) [19-00117]

019 3D Deep Learning approach to predict breast tumor response to chemotherapy using two DCE-MRI volumesM. El Adoui, S. Drisis, M. Benjelloun, Univ. of Mons; Inst. Jules Bordet, Brussels (BE) [2]

020 Development of automated estimation of dispro-portionately enlarged subarachnoid space in head CTN. Takahashi, T. Kinoshita, Y. Shinohara, T. Ohmura, E. Matsuyama, H. Toyoshima, Research Inst. of Brain and Blood Vessels, Akita; Int. Univ. of Health and Welfare, Ohtawara (JP) [13]

021 Fast and automatic liver segmentation for inter-ventional oncology procedures of liver cancerA. Landreau, F. Lalys, Y. Rolland, H. Hammami, Therenva SAS; Centre Eugène Marquis, Rennes (FR) [19]

022 Primary technical efficacy of stereotactic micro-wave ablation compared to non-navigated conven-tional MWA for ablation of liver malignancies.L. Luerken, L. Beyer, J. Schaible, C. Stroszczynski, Univ. Hosp. Regensburg (DE) [26]

023 Segmentation of glandular area in clinical mam-mograms using deep learning aimed at volumetric breast density measurementM. Yamamuro, Y. Asai, N. Yasuda, K. Yamada, K. Saka-guchi, T. Konishi, Y. Ozaki, M. Matsumoto, T. Murakami, Kindai Univ. Hosp., Osaka; Kyoto Prefectural Police Hq.; Osaka Univ. Graduate School of Medecine; Kobe Univ. (JP) [28]

024 Feasibility of 2D-3D intensity-based rigid regis-tration for liver radioembolization guidanceH. Hammami, F. Lalys, Y. Rolland, P. Haigron, Therenva SAS; Centre Eugène Marquis, Rennes; Univ. of Rennes 1 (FR) [32]

025 Dose distribution analysis of hybrid intensity-modulated radiation therapy for locally advanced lung cancerY. Okamoto, K. Takahara, Osaka Police Hosp. (JP) [33]

026 Model-based Registration of Deaeration Defor-mation for in vivo Animal LungsK. Kobayashi, M. Nakao, J. Tokuno, T. F. Chen-Yoshikawa, H. Date, T. Matsuda, Kyoto Univ.; Kyoto Univ. Hosp. (JP) [40]

027 Ultrasonic image-guided robotic system for nerve block anesthesiaS. Chen, Y. Lin, Shanghai Jiao Tong Univ. (CN) [44]

028 Effects of super resolution processing using deep learning technique for SPECT imagesY. Okura, M. Yamamoto, R. Hashimoto, Hiroshima Interna-tional Univ. (JP) [78]

029 First approach to analyse the body fluid status automaticallyK. Skerl, J. Schwarz, T. Fritz, V. Oppelt, S. Uharek, R. Celik, Furtwangen Univ., Villingen-Schwenningen; Ortenau Klinikum, Offenburg (DE) [102]

030 Development of Automatic Assessment Method for Meniscus in UltrasonographyH. Watanabe, N. Hayashi, M. Shimosegawa, T. Ogura, N. Nakamura, M. Ogawa, N. Takagi, N. Tanki, Gunma Prefectural College of Health Sciences, Maebashi; Kaihin Orthopedic and Rheumatism Clinic, Chiba; Teikyo Univ. Chiba Medical Center, Ichihara; Butsuryo College of Osaka, Sakai (JP) [110]

031 Computerised volumetric breast density meas-urements based on anatomical knowledge on digital mammogramsY. Asai, M. Yamamuro, N. Yasuda, K. Yamada, Y. Ozaki, M. Matsumoto, T. Murakami, Kindai Univ. Hosp., Osaka; Kyoto Prefectural Police Hq.; Osaka Univ. Graduate School of Medicine; Kobe Univ. School of Medicine (JP) [31]

032 3D fully convolutional network-based head structure segmentation on multi-modal images from sparse annotationK. Mori, T. Sugino, H. Roth, M. Oda, T. Kin, Nagoya Univ.; The Univ. of Tokyo (JP) [116]

033 Intravoxel incoherent motion perfusion magnetic resonance imaging of water molecules in the rat cortex after common carotid artery occlusion at 11.7TS. Fujiwara, Y. Mori, D. M. de la Mora, K. Yoshida, K. Ogasawara, Y. Yoshioka, Iwate Medical Univ., Morioka; Osaka Univ. (JP); Univ. of Copenhagen (DK) [123]

034 Semi-automated small intestine segmentation by fully convolutional networks and Hessian analysisK. Mori, H. Oda, T. Sugino, K. Nishio, K. Chiba, K. Oshima, T. Kitasaka, M. Oda, C. Shirota, A. Hinoki, H. Uchida, Nagoya Univ.; Nagoya Univ. Graduade School of Medicine; Aichi Inst. of Technology, Toyota (JP) [133]

035 Can thin-slice diffusion weighted imaging promise reliable measurement of apparent diffusion coefficient? : phantom studyT. Yoshida, A. Urikura, Y. Hosokawa, K. Shirata, Y. Nakaya, M. Endo, Shizuoka Cancer Center, Nagaizumi; Hirosaki Univ. (JP) [139]

036 Preliminary Study on Extraction of Blood Vessels from Fluoroscopic Images Using Deep Convolutional Neural NetworkR. Kimura, N. Matsubara, A. Teramoto, K. Saito, T. Ohno, H. Fujita, Fujita Health Univ., Toyoake; Fujita Health Univ. Bantane Hosp., Nagoya; Gifu Univ. (JP) [140]

037 Automated Segmentation of Prostate Gland with Superpixel based and Active Contour based Method-ology using Diffusion-Weighted MR ImagingA. Mehndiratta, D. Singh, S. Bhattacharya, C. J. Das, V. Kumar, A. Singh, Indian Inst. of Technology Delhi; All India Inst. of Medical Sciences Delhi, New Delhi; Amity Univ., Noida (IN) [157]

038 Detection of Spinal Ultrasound Landmarks Using Convolutional Neural NetworksM. Asselin, V. Wu, T. Ungi, G. Fichtinger, Queen’s Univ., Kingston, ON (CA) [205]

039 Segmentation of uterus and uterine fibroids in MR images using convolutional neural networks for HIFU surgery planningG. Yang, C. Zhang, H. Shu, Y. Liu, Y. Wen, Q. Zhang, J. L. Dillenseger, Southeast Univ., Nanjing; Chongqing Medical Univ.; National Engineering Research Center of Ultrasound Medicine; Chongqing Weihai Software Develop-ment Co. Ltd., Chongqing (CN); Univ. of Rennes 1 (FR) [210]

040 Segmentation of aorta dissection CT images using convolution neural networksG. Yang, X. Zhao, T. Lv, H. Shu, P. Haigron, Southeat Univ., Nanjing (CN); Univ. of Rennes 1 (FR) [212]

041 Measurement of pressure value in mammograph-ic breast compressionH. Nishide, S. Sugiura, Gifu Univ. of Medical Science, Seki (JP) [220]

042 Segmentation of Hepatic arterial Cone-beam CT Angiography: Comparison of vessels enhancement methodsS. Toure, E. Curti, Y. Rolland, H. Saint-Jalmes, J. Bézy-Wendling, P.-A. Eliat, Univ. of Rennes 1 (FR) [19-00061]

043 Towards Developing a New Diffeomorphism Strategy for Non Rigid Medical Image RegistrationS. Dakua, J. Abinahed, A. Zakaria, A. Al-Ansari, F. Ben-saali, A. Amira, X. Zhai, P. Coveney, R. Richardson, Hamad Medical Corp.; Qatar Univ., Doha (QA); Univ. of Essex; Univ. College London (GB) [19-00068]

044 Design and Clinical Test of a Passive Ultrasound Probe Holder Mechanism for Ultrasonography Guided Arterial PuncturingB.-J. Yi, M. U. A. Khan, Hanyang Univ., Ansan (KR) [19-00077]

045 Regional-surface-based registration for image-guided neurosurgery: Effects of scan modes on registration accuracyY. Dong, C. Zhang, D. Ji, M. Wang, Z. Song, Fudan Univ., Shanghai (CN) [19-00106]

046 Analysis and Optimization of the Robot Setup for Robotic-Ultrasound-Guided Radiation TherapyM. Schlüter, S. Gerlach, C. Fürweger, A. Schlaefer, Univ. of Technology Hamburg-Harburg; European Cyberknife Center Munich (DE) [19-00122]

047 A novel RBF-based predictive tool for facial dis-traction surgery in growing children with syndromic craniosynostosis.F. Angullia, R. Fright, R. Richards, S. Schievano, A. Linney, D. Dunaway, Great Ormond Street Hosp. for Children, London; Univ. College London (GB) [219]

048 Segmentation of liver parenchyma in ultrasound images for automatic diagnosis of liver cirrhosisT. Imaizumi, N. Koizumi, Y. Nishiyama, N. Matsumoto, M. Ogawa, The Univ. of Electro-Communications; Nihon Univ. Hosp., Tokyo (JP) [19-00095]

ISCAS

049 Sucker design improvement of stiffness-adjusta-ble grasping pads for laparoscopic surgeriesY. Nakajima, K. Sukondhasingha, Tokyo Medical and Dental Univ. (JP) [112]

050 Improved laparoscopic access guidance for Verres needle procedures by means of proximally attached audio evaluationA. Illanes, A. Schaufler, A. Boese, C. Wex, R. Croner, M. Friebe, Otto-von-Guericke Univ., Magdeburg (DE) [163]

051 Bleeding and Hemostasis Region Extraction using a Support Vector Machine for Automatic Hemostasis Surgery with Abdominal Cavity IrrigationY. Matsunaga, T. Igarashi, R. Nakamura, Chiba Univ. (JP) [79]

052 Global patient tracking with trifocal reconstruc-tion in computer-assisted ENT-surgeryG. Diakov, W. Freysinger, Innsbruck Medical Univ. (AT) [24]

053 Endoscopic vs. volumetric OCT imaging of the mastoid bone structure for pose estimation in mini-mally invasive cochlear implant surgeryM.-H. Laves, S. Latus, J. Bergmeier, T. Ortmaier, L. A. Kahrs, A. Schlaefer, Leibniz Univ. Hannover; Univ. of Technology Hamburg-Harburg (DE) [19-00109-P]

054 Integration of intra-operative brain functional positions into the standard brain using SPMK. Ohshima, I. Sato, Y. Nambu, Y. Fujino, Y. Horise, K. Kusuda, M. Tamura, Y. Muragaki, K. Masamune, Future Univ. Hakodate; Tokyo Women’s Medical Univ. (JP) [197]

055 An automatic unmarked guidewire navigation: application to a remote-controlled vascular interven-tional robot systemL. Gu, Y. Ma, C. Wang, H. Shen, S. Zhou, H. Xie, L. Xie, Shanghai Jiao Tong Univ.; Chinese Academy of Sciences, Shenzhen; Peking Union Medical College Hosp. (CN) [223]

056 Improvement of Intraoperative plantar pressure measuring system considering physiological load conditionI. Sakuma, I. Hosoi, E. Kobayashi, S. H. Chang, T. Matsu-moto, Q. An, E. Anzai, Y. Ohta, The Univ. of Tokyo; Tokyo Women’s Medical Univ.; National Inst. of Advanced Sci-ence and Technology; Ochanomizu Univ., Tokyo (JP) [124]

057 3D printed model-based simulation of laparo-scopic surgery for cancer of the descending colon with an abdominal aortic aneurysm: A new surgical techniqueD. Hojo, M. Hiyoshi, T. Nishikawa, S. Emoto, H. Nozawa, K. Kawai, K. Hata, T. Tanaka, Y. Shuno, M. Kaneko, K. Sasaki, K. Murono, H. Sonoda, S. Ishihara, The Univ. of Tokyo (JP) [93]

058 Impact of a motorised articulated laparoscopic needle holder with ergonomic handle on the gesture smoothness: a pilot studyA. Dufaug, L. Goujon, C. Barthod, Univ. Savoie Mont-Blanc, Annecy (FR) [18-00640]

059 A Generic Cable-Driven Manipulator for Targeted Transrectal MR-guided Prostate Biopsy: Preliminary Design and Intervention PlanningN. Navkar, J. D. V. Garcia, C. Velasquez, S. Balakrishnan, J. Abinahed, W. El Ansari, K. Al-Rumaihi, A. Darweesh, A. Al-Ansari, N. Tsekos, M. Karkoub, Univ. of Houston, TX (US); Hamad Medical Corp.; Texas A&M Univ., Doha (QA) [56]

060 Development of Mechanical 3D Ultrasound Scan-ning Devices for Image-guided InterventionsA. Fenster, J. Rodgers, D. Gillies, J. Kishimoto, S. Papernick, N. Kakani, Western Univ., London, ON (CA); Manchester Royal Infirmary (GB) [72]

061 A robotic surgical arm dockable on an endoscope to prevent organ injury during insertionD. H. Lee, M. Hwang, J. H. Kim, D. S. Kwon, Korea Ad-vanced Inst. of Science and Technology, Daejeon (KR) [109]

062 Design of 4-DOFs master device and preliminary test for flexible endoscopic robot surgeryJ. Ahn, J. Kim, H. Kim, D. S. Kwon, Korea Advanced Inst. of Science and Technology, Daejeon (KR) [217]

063 Design, Characterization and Optimization of a Soft Fluidic Actuator for Minimally Invasive SurgeryG. Decroly, B. Mertens, P. Lambert, A. Delchambre, Univ. Libre de Bruxelles, Brussels (BE) [19-00051]

064 Design of a parametric knee implant model based on Active Shape Model output data for indi-vidualized knee implantsP. Sembdner, L. Mika, S. Heerwald, S. Holtzhausen, R. Stelzer, Dresden Univ. of Technology; Dornheim Medical Images GmbH, Magdeburg (DE) [132]

065 Augmented reality guidance for zygomatic implant navigation system based on fully-tracked strategyX. Chen, Q. Sun, P. Sun, Y. Gao, Shanghai Jiao Tong Univ. (CN) [19-00100]

066 Cerebral white matter abnormalities can affect cognitive improvement after carotid endarterectomy in carotid artery steno-occlusive patientsJ. Yoshida, F. Yamashita, M. Sasaki, K. Yoshioka, S. Fujiwara, M. Kobayashi, K. Yoshida, Y. Kubo, K. Ogasawara, Iwate Medical Univ., Morioka (JP) [55]

067 Development of brain surgery assistance system that integrate forceps with continuous tumor resec-tion function and tumor cell isolation deviceT. Nagame, A. Hanafusa, T. Koguchi, F. Shimizu, K. Masamune, Y. Muragaki, H. Iseki, K. Nomura, Shibaura Inst. of Technology, Saitama; Tokyo Women’s Medical Univ.; Waseda Univ., Tokyo (JP) [125]

068 Augmented reality-assisted ventricular puncture with marker-based scene registrationC. Kunz, M. Schneider, M. Hlavac, D. Zenth, I. Gergel, C. Pylatiuk, B. Hein, Karlsruhe Inst. of Technology; Univ. of Ulm; User Interface Design GmbH, Munich; mbits imaging GmbH, Heidelberg (DE) [158]

069 Volume rendering depth mapping for fast vessel identification during intracranial deep electrode planningA. Higueras-Esteban, I. Delgado-Martínez, L. Serrano, G. Conesa, M. A. Gonzalez Ballester, L. Serra, Galgo Medical S.L.; Univ. Pompeu Fabra; Hosp. del Mar, Barcelona (ES) [170]

070 Accuracy Evaluation of a Drill Guidance System for Orthopaedic SurgeryI. Georgilas, N. Sell, J. Bridgwater-Court, G. Giddins, J. du Bois, Univ. of Bath (GB) [19-00111]

071 Three-Dimensional Displacement after a Medial-izing Calcaneal Osteotomy in relation to the Hindfoot Alignment and Osteotomy AngleA. Burssens, M. Peiffer, C. Belvedere, S. Clockaerts, T. Leenders, A. Leardini, W. I. Group, E. Audenaert, J. Victor, Univ. Hosp. Ghent; AZ Groeninge, Kortrijk; AZ Monica, Deurne (BE); Istituto Ortopedico Rizzoli, Bologna (IT); Hosp. Rummelsberg, Schwarzenbruck (DE) [49]

072 Robust 3D kinematic measurement of femoral component using machine learningT. Yamazaki, T. Tomita, Y. Sato, H. Yoshikawa, K. Sugamoto, Saitama Inst. of Technology, Fukaya; Osaka Univ. Graduate School of Medicine; Nara Inst. of Science and Technology, Ikoma (JP) [127]

073 Towards a markerless Computer Assisted Ortho-paedic Surgery systemS. Sta, G. Dardenne, J. Ogor, J. Bert, H. Letissier, E. Stindel, C. Hamitouche, IMT Atlantique, Plouzané; LaTIM; INSERM, Brest (FR) [186]

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ISCAS Executive Board: President: Kensaku Mori (Japan); General Secretary: Cristian A. Linte (USA)

Marta Kersten (Canada); Ichiro Sakuma (Japan); Ken Masamune (Japan); Caroline Essert (France); Pierre Jannin (France); Purang Abolmaesumi (Canada)Georg Eggers (Germany)

ISCAS Advisory Board: Kevin Cleary (USA); Takeyoshi Dohi (Japan); Gabor Fichtinger (Canada); Masakatsu Fujie (Japan); Makoto Hashizume (Japan); Javier Herrero (Spain); Leo Joskowicz (Israel); Young Soo Kim (Korea); Thomas Lango (Norway); Heinz U. Lemke (Germany); Lena Maier-Hein (Germany); Nassir Navab (Germany); Terry Peters (Canada); Guang Zhong Yang (GB)

Honorary Members: Takeyoshi Dohi (Japan); Toyomi Fujino (Japan); Chiaki Hamanishi (Japan); Thomas Lambrecht (Switzerland); Heinz U. Lemke (Germany); Pierre Rabischong (France); Kintomo Takakura (Japan); Michael W. Vannier (USA)

The International Society for Computer Aided Surgery is a non-profit organization aiming to help global collaborations and facilitate communications among our colleagues in the fields of computer-aided surgery and related medical interventions.

Join ISCAS and save on our negotiated rates and services

>> Reduced registration for CARS Conferences being held in Europe, Asia and United States>> Reduced subscription to the International Journal of Computer Assisted Radiology and Surgery>> Priority reservations and discounts on ISCAS events

International Society for Computer Aided SurgeryPresident: Kensaku Mori (Japan)

www.iscas.net

ISCAS activities:

>> ISCAS/CARS annual conference>> Student awards and scholarships>> Workshops >> Affiliation with scientific journals

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Poster Session

091 Towards automatic lesion classification in the upper aerodigestive tract using OCT and deep transfer learning methodsM. Schlüter, N. Gessert, S. Latus, V. Volgger, C. Betz, A. Schlaefer, Hamburg Univ. of Technology; Ludwig- Maximilians-Univ. Munich; Univ. Medical Center Hamburg-Eppendorf (DE) [35]

092 Detection of lung nodules and suprahyoid head and neck lesions in high-resolution CT scans E. Kapoor, M. Khanna, George Washington Univ., Washing-ton, DC (US) [206]

093 Discrimination of the invasive of lung adenocarci-noma in computed tomography image using homology methodK. Nakane, S. Tomohisa, H. Numasaki, M. Koizumi, H. Yamamoto, O. Honda, M. Yanagawa, N. Tomiyama, Osaka Univ. (JP) [81]

094 Deep generative model-based unsupervised detection of inappropriate images in a chest X-ray datasetT. Nakao, S. Hanaoka, Y. Nomura, M. Murata, T. Takenaga, S. Miki, T. Watadani, T. Yoshikawa, N. Hayashi, O. Abe, The Univ. of Tokyo Graduade School of Medicine; The Univ. of Tokyo Hosp. (JP) [92]

095 Improvement of classification performance of pulmonary nodules in CT images using multiple deep convolutional generative adversarial networksY. Onishi, A. Teramoto, M. Tsujimoto, T. Tsukamoto, K. Saito, H. Toyama, K. Imaizumi, H. Fujita, Fujita Health Univ.; Fujita Health Univ. Hosp.; Fujita Health Univ. School of Medicine, Toyoake; Gifu Univ. (JP) [137]

096 Computer aided diagnosis of cirrhosis and hepa-tocellular carcinoma using multi-phase abdomen CTA. Mehndiratta, A. Nayak, M. Arya, E. Baidya Kayal, J. Culli, S. Krishan, S. Agarwal, Indian Inst. of Technology Delhi, New Delhi; Medanta The Medicity, Gurgaon (IN) [19-00125]

097 Improved method of an automated detection of gastric cancer using FCN and feature based false positive reductionK. Enomoto, A. Teramoto, T. Shibata, K. Saito, H. Fujita, Fujita Health Univ.; Fujita Health Univ. School of Medicine, Toyoake; Gifu Univ. (JP) [138]

098 Automated malignancy analysis of microscopic lung images using a deep convolutional neural net-work and generative adversarial networksA. Teramoto, A. Yamada, Y. Kiriyama, T. Tsukamoto, K. Yan, L. Zhang, R. M.Summers, K. Imaizumi, K. Saito, H. Fujita, Fujita Health Univ., Toyoake; Gifu Univ. (JP); National Inst. of Health; NVIDIA, Bethesda, MD (US) [136]

CMI Poster Session

099 Optimization of the BMD measurement procedure in photo-stimulable phosphor (PSP) digital intraoral imaging systemsA. Katsumata, W. Nishiyama, E. Mikami, T. Hayashi, Asahi Univ. School of Dentistry, Gifu; Media Corp. Ltd, Tokyo (JP) [17]

100 Computer-aided Patient-specific Plate Design Software for Cranial Reconstruction SurgeryS. Park, T. Lee, H. Cho, T. G. Son, W. S. Jeong, J. W. Choi, Y. Kim, Korea Inst. of Science and Technology; Asan Medi-cal Center, Seoul (KR) [27]

101 Web-based platform of planning and visualization for orthognathic surgeryS. Y. Woo, S. J. Lee, J. Y. Yoo, M. H. Choi, W. J. Yi, Seoul National Univ. (KR) [80]

102 Image quality of cone beam CT under different exposure parametersZ. Zhang, F. Wang, X. Xie, L. Zhang, Peking Univ. School and Hosp. of Stomatology; Tsinghua Univ., Beijing (CN) [99]

103 High-quality 3D modeling and its VR animation of skull and jaw using an algorithm of structure from motionY. Hayakawa, K. Nagase, N. Eguchi, R. Hayashi, K. Mizukami, Kitami Inst. of Technology (JP) [118]

104 Automatic Three-Dimensional Cephalometric Annotation System Using Three-Dimensional Convolu-tional Neural NetworksS. H. Kang, K. Jeon, H. J. Kim, J. K. Seo, S. H. Lee, National Inst. of Mathematical Science, Daejon; Yonsei Univ., Seoul (KR) [143]

105 Clinical accuracy of computer guided osteotomy stents in titanium screws drilling in mandibular fracturesH. Abou Elwafa, W. Aboelmaaty, M. Abdelhamid , M. Isaac, K. ElMahdy, Mansoura Univ.; Delta Univ. for Science and Technology, Gamasa; Ministry of Health and Population, Mansoura (EG) [154]

106 Non-invasive computer-assisted dental implant surgery based on optical tracking and 3D printingJ. Pascau, D. García-Mato, S. Ochandiano, S. Espías-Alonso, M. García-Sevilla, R. Moreta-Martinez, J. A. Calvo-Haro, R. Pérez-Mañanes, Univ. Carlos III de Madrid; Univ. Complutense de Madrid (ES) [184]

107 Modified Point- and Surface-based Registration and their Accuracy Evaluation Methods for Computer Assisted Maxillofacial Surgical SystemS. J. Lee, S. K. Yoo, D. J. Moon, J. A. Kim, J. Y. Yoo, M. H. Choi, S. Y. Woo, T. H. Yong, W. J. Yi, Seoul National Univ.; Osong Medical Innovation Foundation, Cheongju (KR) [198]

108 Periodontitis detection and classification in pano-ramic radiographs using Deep Convolutional Neural Network(DCNN)T. H. Yong, S. J. Lee, S. Y. Woo, J. Y. Yoo, M. H. Choi, S. R. Kang, W. J. Yi, Seoul National Univ. Dental Hosp.; Seoul National Univ. (KR) [208]

074 A targeting system for distal locking of intramed-ullary nails based on electromagnetic navigationX. Chen, Y. Gao, H. Wang, Q. Sun, Shanghai Jiao Tong Univ. (CN) [19-00101]

075 Zebra striping and Moiré mapping assessment for hemifacial deformityY. Takeichi, H. Motai, H. Iguchi, K. Hishida, H. Tada, M. Kato, Y. Itoh, Toyota Wakatake General Hosp.; Motai Otorhinolaryngological Clinic, Tokai; Nagoya City Univ.; Wakaba Hosp., Zu; Aichi Medical Univ., Nagakute (JP) [85]

076 Printing of contour-adapted bone scaffolds based on calcium phosphate cementsS. Holtzhausen, S. Heinemann, R. Stelzer, Dresden Univer-sity of Technology (DE) [159]

077 Three-dimensional laparoscopic vision improves forceps motion more in the depth direction than in the horizontal direction.Y. Yamazaki, S. Kanaji, G. Takiguchi, M. Yamamoto, Y. Matsuda, T. Oshikiri, T. Nakamura, S. Suzuki, Y. Kakeji, Kobe Univ. Graduate School of Medicine (JP) [39]

078 New objective skill assessment system for the laparoscopic intestinal anastomosis model and evalu-ation of validityM. Uemura, M. Tomikawa, M. Hashizume, S. Ieiri, M. Eto, Kyushu Univ., Fukuoka; Kagoshima Univ. (JP) [194]

079 Clinical Usability Testing of TTTS Fetal Surgery Planning and Simulation FrameworkJ. Torrents-Barrena, R. López-Velazco, G. Piella, N. Masoller, B. Valenzuela-Alcaraz, E. Gratacós, E. Eixarch, M. Ceresa, M. A. González Ballester, Univ. Pompeu Fabra, Barcelona; Univ. of Barcelona (ES) [119]

080 Introducing surgical landscape guidance for intelligent assistance in minimally-invasive surgery

J. C. Rosenthal, R. Bieck, T. Wittenberg, P. Eisert, T. Neumuth, Fraunhofer Inst. for Telecommunications, Berlin; Innovation Center Computer Assisted Surgery, Leipzig; Fraun-hofer Inst. for Integrated Circuits IIS, Erlangen (DE) [48]

081 Acoustic emission integration for ultrasound guidance: a feasibility study for needle based clinical proceduresA. Illanes, N. Esmaeili, F. Renna, J. Oliveira, M. Coimbra, M. Friebe, Otto-von-Guericke Univ. Magdeburg (DE); Univ. of Porto (PT) [101]

082 Band markers for three-dimensional pose track-ing of catheters using single-view fluoroscopyD. Lee, Korea Inst. of Science and Technology, Seoul (KR) [215]

083 Evaluation of an augmented reality guidance system for laparoscopic liver ablationsK. Cleary, R. Shekhar, X. Liu, W. Plishker, L. W. Lau, Children’s National Medical Center, Washington, DC; IGI Technologies, Inc., College Park, MD (US) [180]

084 Workflow assessment as a preclinical develop-ment tool: surgical process models of three tech-niques for minimally invasive cochlear implantationS. Müller, L. A. Kahrs, J. Gaa, S. Tauscher, M. Kluge, S. John, T. Rau, T. Lenarz, T. Ortmaier, O. Majdani, Leibniz Univ. Hannover; Hannover Medical School (DE) [19-00020]

CAD-AI

085 Proposal for self-evolving CAD system that uses CNNK. Abe, H. Takeo, Y. Nagai, S. Nawano, Kanagawa Inst. of Technology; National Cancer Center Hosp. East, Chiba; International Univ. of Health and Welfare, Tokyo (JP) [5]

086 Quantification of the diagnosis of depression through application of image recognition technologyY. Maki, K. Abe, H. Takeo, Y. Nagai, Kanagawa Inst. of Technology; National Cancer Center Hosp. East, Chiba (JP) [6]

087 Heterogeneity of longitudinal brain imaging phe-notypes in Alzheimer’s disease based on unsuper-vised clustering of blood marker profilesG. Martí Juan, G. Sanroma, G. Piella, Univ. Pompeu Fabra, Barcelona (ES); German Center for Neurodegenerative Diseases, Bonn (DE) [126]

088 Subtype classification of triple negative breast cancers by using radiomic feature and miRNAN. Wada, Y. Uchiyama, Kumamoto Univ. (JP) [57]

089 Automated differential diagnosis of benign and malignant breast lesions on the mammogramsA. Kolchev, I. Egoshin, D. Pasynkov, I. Kliouchkin, O. Pasynkova, Mari State Univ.; Oncology Clinic of Mari El Republic; Kazan Federal Univ., Yoshkar-Ola; Kazan State Medical Univ. (RU) [86]

090 Femur fracture classification from X-ray images with few-shot learning: A preliminary studyC. Lee, J. Jang, Y. Kim, Y. S. Kim, Hanyang Univ.; CTO Information Technology Research Center, Seoul (KR) [111]

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CARS 2019 Tutorials (Special registration required)CARS 2019 Sponsoring

CARS acknowledges the support of the following companies:

Gold Sponsor

Silver Sponsor

Bronze Sponsor

Exhibitors

Partners

TUT1: Tutorial AR/VR: Perceptual Capacities and Constraints in AR/VR for the visualization of 3D biomedical image dataJune 18, 8:30-12:30 Roy Eagleson, PhD; Georges Hattab, PhD

The use of AR and VR modalities for visualization of 3D biomedical image data is feasible thanks to a growing number of hardware and software solutions. As the technical challenges and development hurdles subside, it is increasingly important to consider the special capacities and constraints of the human perceptual, motor, and cognitive systems. From a systems design perspective, empirical research into the human-computer interface performance should inform the development process. We will present essential design notions including, but not limited to, task oriented design, lateral and vertical transformations, and user interface design principles. Generally, this can take the form of “development guidelines” or alternatively, as anti-patterns which alert the designer to the principles that should not be violated. For the purpose of this tutorial, we plan a practical or hands-on session. Given different visu-alization tasks, participants work in small groups to create appropriate visualizations. We anticipate that this could lead to an exploration of the design space. In turn, we could indicate what might benefit from adjustment or be better suited to the task at hand. This tutorial will be a forum for Scientific and Engineering developments in this area, as well as for two talks which overview these different aspects of the field.

TUT2: Tutorial SlicerIGT: Deep learning and computer vision for real-time procedure annotationJune 18, Tuesday 13:30–17:30Tamas Ungi,PhD; Sonia M. Pujol, PhD; Javier Pascau, PhD; Gabor Fichtinger, PhD

SlicerIGT is an established open-source platform for navigation of interventional medical procedures. It has been used to implement experimental and clinical research systems in many specialties from ultrasound-guided injections to brain surgery. The platform supports real time communication with most tracking, imaging, and sensor devices. It also supports communication with major com-mercial navigation systems to experiment with additional features for existing procedures. A series of SlicerIGT tutorials have been presented in the past years, focusing on a different topic each year. This year, the topic is computer vision and deep learning for real time annotation of surgical events. This new feature of SlicerIGT enables detection of tools and gestures in video streams. Video-based data collection can be applied on tools that are not traditionally tracked by optical or electromagnetic sensors. This new feature of SlicerIGT significantly expands the potential applications that can be built on the platform, both in interven-tion navigation and in simulation-based training. The tutorial consists of two sessions. First, invited speakers give an overview of open-source resources and talk about their vision for the future applications of these research tools. In the second session, the audience will build a working surgical simulation software on their laptops, using devices provided by the presenters. Participants will gain hands-on experience in the basics of intervention navigation technology, as well as integration of advanced real-time image processing algorithms.

Sponsored by Intuitive Surgical

TUT3: Tutorial DL-1: Applied Deep Learning for Medical Scientists working with Image DataJune 18, Tuesday 8:30–12:30Daniel Lückehe, PhD; Gabriele von Voigt, PhD

In this tutorial, we would like to show medical scientists how to use methods from the field of deep learning as tools to solve problems in their decisions processes. The tutorial will be designed for about 3-4 hours. As it is impossible to show all aspects in this amount of time, we will focus on the following points:– Introduction to the field of Deep Learning (DL) and neural network implementations with Tensorflow– Hands-on examples for three types of Deep Neural Networks (DNNs) which are especially relevant for the medical field: 1. To classify images - Basic: Convolutional Neural Networks (CNNs) - Advanced: Deep Residual Networks (ResNets) 2. To segment images - U-Net from Convolutional Networks for Biomedical Image Segmentation– Additionally, an outlook to further methods and network architectures like Recurrent Neural Networks to classify time-series will be given

TUT4: Advanced Deep Learning for Medical Imaging Data June 18, Tuesday 13:30–17:30John S.H. Baxter, PhD

This tutorial will focus on the following points: 1) Introduction to complex loss functions and how they relate to the underlying medical imaging problem: Interpret output activation functions and develop losses accordingly, introduce adversarial networks in the context of loss functions and 2) Introduce GANs and discuss mode collapse.

First Session: Advanced Loss Functions– Refresher – final activation layer, loss functions, optimization details– Refresher – creating activation layers and loss functions in Keras / Tensorflow– Advanced activation functions and associated losses – Example – Modifying cross-entropy loss for class balancing – Example – Using a CRF as a final layer with associated loss added to U-Net

Second Session: Adversarial Loss Functions– Motivation – Learning losses rather than inferring them– Adversial optimization – gradient freezing and alternating min-max– Adversarial losses for image generation – Example – MNIST digit generator – Illustratemodecollapseanddiscussramificationsonadversariallosses– Adversarial losses for image reconstruction – Example – CT from sub-sampled C

Third Session: Invited SpeakerInvited talk on advanced topics in Deep Learning.

TUT5: Hands-on tutorial on advanced Deep Learning for Medical ImagingJune 21, Friday 13:30–17:30Nicola Rieke, PhD

Deep Learning is reshaping the healthcare industry and continues to establish itself as the de facto tool for numerous medical applications. This hands-on workshop explores the usage of Deep Learning in Medical Imaging starting from basic Image Classification (Part I) to advanced Data Augmentation and Segmen-tation with Generative Adversarial Networks (Part II). Technical requirements: Important: participants need to bring their own laptop!

Part 1: Image Classification using the MedNIST datasetGet a hands-on practical introduction to deep learning for radiology and medical imaging. You‘ll learn how to:

– Collect, format, and standardize medical image data– Architect and train a convolutional neural network (CNN) on a dataset– Use the trained model to classify new medical images

Upon completion, you’ll be able to apply CNNs to classify images in a medical imaging dataset.

Prerequisites: Basic experience with Python

Part 2: Data Augmentation and Segmentation with Generative Networks for Medical ImagingA generative adversarial network (GAN) is a pair of deep neural networks: a generator that creates new examples based on the training data provided and a discriminator that attempts to distinguish between genuine and simulated data. As both networks improve together, the examples created become increasingly realistic. This technology is promising for healthcare, because it can augment smaller datasets for training of traditional networks. You‘ll learn to:– Generate synthetic brain MRIs– Apply GANs for segmentation– Use GANs for data augmentation to improve accuracy

Upon completion, you‘ll be able to apply GANs to medical imaging use cases. Prerequisites: Experience with CNNs

Sponsored by Nvidia

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Monday, June 17, 2019 8:30 – 18:00

Room Le Réfectoire Room Le Réfectoire

08:00 Registration

08:30 Opening Session

08:40 Modeling and simulationSession Chair: Guillaume Dardenne (FR)

Modeling the non-linearities of flexible endoscopes using machine learningR. Aleluia Porto, F. Nageotte, M. De Mathelin; University of Strasbourg (FR)

Kernel selection in statistical femur modelingA. Asvadi, G. Dardenne, A. Guezou-Philippe, A. Salhi, B. Borotikar, J. Troccaz, V. Burdin; Univ of Western Brittany, IMT Atlantique, University Grenoble Alpes (FR)

Pre-operative planning in acetabular and pelvic ring surgery: the first biomechani-cal modelM. Boudissa, M. Chabanas, H. Oliveri, G. Bahl, J Tonetti; Grenoble University Hospitals, University Grenoble Alpes (FR)

Biomechanical modeling of the lung deflation during minimally-invasive surgeryA. C. Lesage, K. Brock, D. Rice, B. Rigaud, A. Tam, G. Cazoulat; The University of Texas MD Anderson Cancer Center (USA)

10:00 Coffee break

10:30 Keynote lectureChair: Jocelyne Troccaz (FR)

Image guided surgery - inside and outside the ORI. Reinertsen; SINTEF Digital (NO)

11:30 Medical procedures: analysis and evaluationSession chair: Philippe Poignet (FR)

Situation awareness in the “Virtual Operating Room of Errors”: a pilot studyM-S. Bracq, M. Le Duff, E. Michinov, B. Arnaldi, V. Gouranton, P. Jannin ; Univ Rennes, CHU de Rennes (FR)

Preliminary evaluation of haptic guidance for pre-positioning a comanipulated needleH. Gurnel, M. Marchal, L. Launay, L. Beuzit, A. Krupa; University of Rennes 1 (FR)

Analyzing the practice of expert surgeons based on video spatial featuresA. Derathé, S. Voros, F. Reche, P. Jannin, A. Moreau-Gaudry, B. Gibaud; University Grenoble Alpes, CHU de Grenoble, University of Rennes 1 (FR)

12:30 Lunch

13:30 Data fusion and augmented realitySession Cshair: Matthieu Chabanas (FR)

Intraoperative Ultrasound-based Augmented Reality GuidanceJ. Shen, N. Zemiti, C. Taoum, J-L. Dillenseger, P. Rouanet, P. Poignet; University of Rennes 1, University of Montpellier, Institut du Cancer de Montpellier Val d’Aurelle (FR)

3D landmark detection for augmented reality based otologic proceduresR. Hussain, C. Guigou, K. Berihu Girum, A. Lalande, A. Bozorg Grayeli; University of Bourgogne Franche-Comté (FR)

Fusion of X-Ray and patient specific model to assist cardiac resynchronisation therapyN. Courtial, A. Simon, S. Bruge, M. Lederlin, E. Donal, C. Leclercq, M. Garreau; University of Rennes 1, University Hospital Rennes (FR)

14:30 Keynote lectureChair: Jérôme Szewczyk (FR)

Driving and controlling flexible surgical instruments – new developments and challengesEmmanuel Vander Poorten; KU Leuven (BE)

15:30 Coffee break & Poster session

6th SURGETICAConference chairs: Pascal Haigron (FR), Antoine Simon (FR), Pierre Jannin (FR)

6th SURGETICAConference chairs: Pascal Haigron (FR), Antoine Simon (FR), Pierre Jannin (FR)

15:30 Poster session

Statistical shape model of vascular structures with abdominal aortic aneurysmC. Dupont, C. Boichon-Grivot, A. Kaladji, A. Lucas, M. Rochette, P. Haigron; University of Rennes 1, Ansys France (FR)

Pelvic parameters measurement with sterEOS: a preliminary reliability studyM. Dorniol, G. Dardenne, A. Guezou-Philippe, H. Letissier, C. Lefevre, E. Stindel; Universi-ty Hospital Brest, University of Western Brittany (FR)

Extended field-of-view of the knee bone surface using ultrasoundM. Nasan, Y. Morvan, G. Dardenne, J. Chaoui, E. Stindel; University of Western Brittany, University Hospital Brest, IMASCAP (FR)

Towards a patient-specific simulation of the balloon angioplasty treatment techniqueB. Al-Helou, C. Dupont, A. Bel-Brunon, W. Ye, A. Kaladji, P. Haigron; University of Rennes 1, University Lyon, ANSYS (FR)

Nervous System Exploration Using Tractography To Enhance Pelvic SurgeryC. Muller, A. Delmonte, P. Meignan, Q. Peyrot, A. Virzi, L. Berteloot, D. Grevent, T. Blanc, P. Gori, N. Boddaert, I. Bloch, S. Sarnacki; Université Paris Descarte, Necker Hospital, Université Paris-Saclay (FR)

Transvaginal Uterine Biopsy: Robot ComanipulationN. Tajeddine, M-A. Vitrani, R, Chalard; Sorbonne Université, Univ Paris 06 (FR)

Surface imaging for patient positioning in radiotherapyS. Nazir, J. Bert, D. Visvikis, Hadi Fayad; University of Western Brittany, Hamad Medical Corporation OHS, PET/CT center Doha (FR-QA)

Orientability evaluation of concentric tube robots deployed in natural orifices Q. Peyron, K. Rabenorosoa, N. Andreff, P. Renaud; University of Strasbourg, University of Franche-Comté (FR)

Computer Assisted Early Diabetic Retinopathy Detection from Retinal Fundus Im-age using Transfer Learning ModelB. Kumar, S. Kumar, Rajeev Gupta; MNNIT Allahabd (IN)

Simulation for preoperative planning, balloon inflation for tibial plateau fracture reductionK. Aubert, T. Vendeuvre, M. Rochette, P. Rigoard, A. Germaneau; Université de Poitiers, ANSYS France, CHU Poitiers (FR)

Computer Assisted Detection of Good View Frame from USG Video for ONSD Meas-urementB. Kumar, M. Singh, R. Gupta; MNNIT Allahabd (IN)

Patient’s specific computer simulations to assist coronary artery bypass surgery A. Drochon, A. Anselmi, H. Corbineau, J-P. Verhoye; Univ Technologie Compiègne, University Hospital Rennes (FR)

CFD based study of blood stagnation caused by LVAD inflow cannula angulation A. Ben Abid, V. Morgenthaler, P. Haigron, E. Flecher; University of Rennes 1, University Hospital Rennes, ANSYS France (FR)

Transesophogeal HIFU cardiac fibrilation therapy guidance by two perpendicular US imagesB. Dahman, J.-L. Dillenseger; University of Rennes 1 (FR)

Potential of global vision system for learning laparoscopy surgical skills S. Vijayan, E. Keddiseh, B. Trilling, S. Voros; University Grenoble Alpes (FR)

Segmenting Surgical Tasks using Temporal Convolutional Neural NetworkM. Millan, J. Szewczyk, C. Achard; Sorbonne Université (FR)

An Experimental Protocol on Attentional Abilities in Classic and Robot-Assisted LaparoscopyE. Ferrier-Barbut, V. Luengo, M-A. Vitrani; Sorbonne Université (FR)

Mixed Reality Experiment for Hemodialysis TreatmentC. Lohou, M. Bouiller, Emilie Gadea-Deschamps; Université Clermont Auvergne, Centre Hospitalier Emile Roux, le Puy-en-Velay (FR)

Image-based registration for lung nodule localization during VATSP. Alvarez, R. Simon, M. Chabanas, Y. Payan, J.-L. Dillenseger; University of Rennes 1, University Grenoble Alpes, University Hospital Rennes (FR)

Additive Manufacturing of a Microbiota Sampling Capsule Based on a Bistable MechanismM. Ben Salem, G. Aiche, L. Rubbert, T. Soranzo, P. Cinquin, D. K. Martin, P. Renaud, Y. Haddab; University of Montpellier, University of Strasbourg, University of Grenoble Alpes (FR)

Towards a novel man-machine interface to speed up training on robot-assisted surgeryG. Gil, J. Walker, N. Zemiti, A. Okamura, P. Poignet; University of Montpellier, Stanford University (FR-USA)

Percutaneous osteoplastyJ. Garnon, L. Meylheux, B. Bayle, A. Gangi; University of Strasbourg (FR)

Development of a finite element model of prostate validated by a realistic prostate phantomM. Dieng, G. Chagnon, S. Voros; University Grenoble Alpes (FR)

FEM-based confidence assessment of non-rigid registrationP. Baksic, H. Courtecuisse, M. Chabanas, B. Bayle; University of Strasbourg, University Grenoble Alpes (FR)

Tumor heterogeneity estimation from DW-MRI and histology data by linking macro- and micro-information in a quantitative wayY. Yin, O. Sedlaczek, K. Breuhahn, I. Vignon-Clementel, D. Drasdo; INRIA Paris, University Hospital of Heidelberg (FR-GE)

Improved prostate cancer radiotherapy planning with decreased dose in a rectal sub-region highly predictive for toxicity O. Acosta, C. Lafond, A. Barateau, B. Houede, A. Largent, E. Mylona, N. Perichon, N. Delaby, P. Haigron, R. de Crevoisier; University of Rennes 1 (FR)

Experimental test bench for the hemodynamic study of coronary arteries: bifurca-tion, stent, aneurysmM. Lagache, R. Coppel, A. Gomez, G. Finet, J. Ohayon; University Grenoble Alpes, Univer-sité Savoie Mont Blanc, Université Claude Bernard, Lyon (FR)

17:15 Robotics and mechatronicsSession Chair: Pierre Renaud (FR)

X-ray free breach detection in robot-assisted spine surgery with real-time con-ductivity sensingJ. Da Silva, F. Richer, V. Kespern, T. Chandanson, G. Morel; SpineGuard, Sorbonne Université (FR)

Toward a design method for tensegrity-based medical robotsJ. Begey, M. Vedrines, N. Andreff, P. Renaud; ICube, University of Strasbourg, University of Franche-Comté (FR)

Bright pill: ingestible biorobot using light to control therapeutic molecule release produced by embarked bacteriaT. Soranzo, G. Aiche, C. Caffaratti, D. Martin, P. Cinquin, Y. Haddab; University Grenoble Alpes, University of Montpellier (FR)

18:10 Surgetica Welcome Reception

20:00 Surgetica Dinner

08:30 Image processing and registrationSession Chair: Jean Louis Dillenseger (FR)

Robust tracking of tissues for flexible endoscopyX. T. Ha, P. Zanne, F. Nageotte; University of Strasbourg (FR)

Investigating the Role of Helical Markers in 3D Catheter Shape Monitoring from 2D FluoroscopyA. E-T. Yang, J. Szewczyk; Sorbonne Université (FR)

Localization of brachyterapy seeds in TRUS images using rigid priors and medial forcesV. Jaouen, J. Bert, A. Valeri, D. Visvikis; Inserm, Université de Bretagne Occidentale, CHRU Brest (FR)

Automatic segmentation of intraoperative ultrasound images of the brain using U-NetF.-X. Carton, J. Noble, B. Munkvold, I. Reinertsen, M. Chabanas; Univ Grenoble Alpes, Vanderbilt Univ, Norwegian Univ of Science and Technology, SINTEF (FR-NO)

10:00 Coffee break

10:30 Invited lectureChair: Jean-Philippe Verhoye (FR)

Data-driven solutions for deep brain stimulation surgeryClément Baumgarten; University of Rennes 1, University Hospital Rennes, LTSI – INSERM UMR 1099

11:15 Navigation and interventional planningSession Chair: Marie-Aude Vitrani (FR)

Real-time Prediction of High-risk Instrument Motion based on Location InformationY. Sawano, N. Ohtori, Ryoichi Nakamura; Chiba University, Jikei University School of Medicine, Japan Science and Technology Agency (JP)

Transcranial robot-assisted Blood-Brain Barrier opening with Focused UltrasoundG. Thomas, L. Barbé, P. Agou, B. Larrat, J. Vappou, F. Nageotte; Université de Strasbourg (FR)

Accurate Instrument Tracking in Minimally Invasive SurgeryM. Arico, G. Morel; Sorbonne Université (FR)

12:15 Closing session12:30 End of Surgetica

Tuesday, June 18, 2019 08:30 – 12:30

cars 2019 rennes, france€¦ · rennes, france program. 3 jun 18–21 2019 ouven e acobin enne...

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