IGP NCRR Ellisman Laboratory 3D Microscopy Data Electron tomography Large data sets Heterogeneous collection of data/scientific questions Goal: segmentation & visualization of cells and subcellular structures IGP NCRR EMT Data Projection Reconstruction (FBP) Manual Segmentation Direct Volume Rendering IGP NCRR EMT Data Gap Junctions Actin Fibers IGP NCRR Ellisman Collaboration Activities Meetings at NCMIR February 2006: Discuss segmentation app. ideas July 2006: Preview segmentation app. prototype, interview users, discuss research ideas Software development Segmentation / visualization application Collaborative activities Visualize gold-labeled data Segmentation of spiny dendrite data (ongoing) Segmentation of mitochondria data (ongoing) IGP NCRR Visualization Visualizing Gold Particles in EMT Data IGP NCRR Segmentation Application Motivation Concrete progress on Ellisman collaboration Designed in consultation with NCMIR staff Generalize functionality Wide range of applications within the CIBC and elsewhere Design strategy Comprehensive 3D interface Photoshop look and feel, layers Tools for manual interaction Hooks to wide variety of ITK algorithms IGP NCRR Segmentation Application Image Data Image Data Stack of Image Volumes Layered Slice Visualization 3D Visualization Stack of Image Volumes Layered Slice Visualization 3D Visualization Select Layers Set Parameters Select Layers Set Parameters Manual Input Manual Input ITK Filters Teem Filters Custom Filters ITK Filters Teem Filters Custom Filters Contouring and Painting Contouring and Painting ITK File I/O Resampling And Streaming Resampling And Streaming Processed layer returned to stack as new layer IGP NCRR Segmentation Application Demo 5 mins IGP NCRR Capecchi Laboratory Impact Genetics, development, cancer Expand the scope of questions Challenges High-throughput User-assisted/automated tools Quantitative microCT Approach Processing pipeline Progression of tools Eviscerated Mouse Paw IGP NCRR Capecchi Collaboration Activites Regular meetings with Capecchi lab staff and students Segmentations of wild-type and homozygous (Hox d11) mutant forelimbs Paper in progress: length comparison (digital) of mutant and wild-type forelimb bones IGP NCRR Capecchi Collaboration Activities Shape analysis algorithms Paper accepted: Workshop on Mathematical Foundations of Computational Anatomy 2006 Shape analysis library Particle system and shape analysis code for ITK (supported locally by CIBC and NAMIC) Integrate into CIBC Segmentation application Shape analysis of hoxd11 vs. wild-type mouse forelimb bones IGP NCRR Capecchi Collaboration Activities Image-basedOriginal Meta P P P Preliminary results for digit 2 from the image-based bone-length comparison study. Expressed as the ratio of the average length of the mutant bone to the average length of the wild type bone. Normalized with respect to the length of an individual specimen's humerus. IGP NCRR Capecchi Collaboration Activities Homozygous Mutant Wild Type Segmentations of wild type and homozygous mutant bones of the second digit of the left mouse forelimb. IGP NCRR Capecchi Collaboration Activities Length measurement of the mouse humerus using SCIRun. IGP NCRR Capecchi Collaboration Plans A shape analysis pipeline for mouse phenotyping Open-source particle system library (Winter 2006) Further shape analysis research (ongoing) Specific scientific results for skeletal phenotyping with the Capecchi Laboratory Finish forelimb segmentations (Fall 2006) Bone length comparison paper (Fall 2006) Shape study of mouse bones (ongoing) IGP NCRR Related Project: Bridge Reconstruction and visualization of microtubules from FLM Original Deconvolved Visualization of Block Traversal of Tubuli IGP NCRR Related Projects: Chien,Marc Tracking of axons in SBFEMDeformable tiling and registration of serial section TEM Papers to appear in MICCAI 2006 Workshop on Microscopic Image Analysis IGP NCRR IGP NCRR Image and Geometry Processing Highlights of ongoing work Geometry processing Shape analysis Visualization/segmentation IGP NCRR Geometry Processing/Modeling IGP NCRR MRI Head Segmentation Applications Bioelectrical fields Neuroscience, neurology, psychiatry State of the art Parametric statistics (EM) Inhomogeneity correction MRF (regularization) Atlas-based prior (registration) Our goals Improve robustness/accuracy -> usability Robust, ubiquitous implementations Integrate into processing pipeline IGP NCRR Segmentation Research Neighborhood statistics Manifolds in high-dimensional spaces Filtering, compression, segmentation, visualization Strategy Nonparametric density estimation Engineering issues IGP NCRR Image Filtering Reduce entropy PDF of image neighborhoods Process that learns underlying image structure (UINTA) Awate, Whitaker, CVPR, 2005 Awate, Whitaker, PAMI 2005 Include MRI noise model for a posteriori estimation Awate, Whitaker, IPMI 2005 IGP NCRR MRI Head Segmentation Tasdizen, Awate, Foster, Whitaker, MICCAI 2005 (under review) MRI Input GM, WM, CSF Seg. Comparison: SOTAEM w/MRFs & Atlas (Leemput et al.) GM Classification Performance vs Noise Level Collab: Makeig-Worrell, Wolters, Warfield, McIntyre %1%3%5%7%9% ProposedLeemput IGP NCRR Cell Segmentation Nonparametric density estimation image neighorhoods Texture Partition image to reduce in-class entropy Random initialization Fast (nonlocal) level-set method Collab: NCMIR, Marc IGP NCRR Peters et al., 2002 Modeling DW-MRI David Tuch, MGH Q-Ball Imaging Computational microanatomy Reproduce DW-MRI measurements through simulation Impact DW MRI for the study of neurological disorders (e.g. dementia) Scientific/clinical inferences Image acquisition Challenges Generating realistic anatomies Controling relevant parameters Generating sufficient statistics Scale IGP NCRR Preliminary Results Strategy Generate statistically accurate geometry Continuum model Parameters from literature (radii, g- ratios, etc.) FA = 0.44 FA = 0.55 FA = 0.73 Axon fibers IGP NCRR Motivation and Philosophy Research and Development Integration and Applications Progress Summary IGP NCRR