Bio image Informatics

Amali Upendra Rathnapriya114114U

Faculty of Information TechnologyUniversity Of Moratuwa

06.06.2014

Overview• What are Bio images• Capturing bio images• Why it is Bio image Processing • Techniques used in Bio image Processing• Evaluation methods of techniques• Application areas

What are bio images• Why cell imaging is important?

Medical DiagnosticsScientific ResearchesFields of Molecular Biology and Genetics

• Digital imaging systemsMRICTUltra Sound ImagesMicroscopesEndoscopesRadiography

What is bio image processing

• Gathering• Histology• sub cellular location analysis• high content screening• Segmentation• Tracking• Registration of image data

Why is Bio image processing is

distinct? Bio image informatics is the use of computational tools for the process of acquisition, visualization, analysis and distribution of these datasets obtained by imaging modalities

Bio image processing is distinct as its much differentiated from normal images due its comprehensiveness, complexity, delicacy and being critical about accuracy of output due to its applications.

Bio image processing techniques

• Sub-cellular location analysis• Segmentation• Cell Tracking

Sub-cellular location analysis

Characterizing a protein or determining its location within cells is to considerate its function and its sub compartment in different biochemical environments

Sub-cellular location analysis is computational prediction of where a protein resides in a cell

Analysis of the sub-cellular localization of candidates identified in the secretion screens

Methods used in Sub-cellular Location analysis

• Targeting Signal Prediction• Prediction of location based method• Composition based methods of prediction

• Targeting Signal Prediction– Recognizing motifs and receptors in protein transport machinery– Limitation is that its based on individual knowledge and when motifs

are not present can’t predict proteins’ presence

• Prediction of location based method– use a sequence of similar positions (homology) after verified

experimentations assuming that similar proteins ends up in similar sub cellular locations.

– But still there can be known exceptions.

• Composition based methods of prediction– proxy based approach where amino acid composition is used as a

proxy for protein location– can be applied to any set of compartments and proteins, provided

one has enough data

Segmentation • Generation of a representation over a selected

feature space and the assignment of pixels to one of the model components or segments to model the distribution of data using parametric models.

Transform methods such as watershed segmentation

Illustration of 3D cell nuclei segmentation on a 2D slice

Methods used in Segmentation

• Amplitude segmentation based on histogram features• Edge based segmentation• Region based segmentation

• Amplitude segmentation– Based on tresholding on histogram and tresholding of gray level for a region

having uniform brightness against a region having different gray levels and brightness.

– Obtaining correct threshold values is difficult in order to obtain proper segmentation results.

• Edge based segmentation– identifying edges the boundaries of regions are detected by marking of

discontinuities in gray level, color– Performance is affected by noise and weak edges and fake edges have a

negative influence on accuracy of segmented image. • Region based segmentation

– Pixels with similar properties are clustered together to obtain a homogenous region by region merging and region splitting evaluating neighborhood pixels.

– There can be instances where under segmentation and over segmentation of regions in the image can occur

Cell Tracking Tracking tools yield sequence of coordinates

indicating the position of each tracked object at each time point as the result of cell tracking

Single cell tracking of a mammalian

cell tracking sample trajectory metastatic cancer

Methods used in Cell Tracking

• Morphology measures• Velocity Measures• Diffusivity Measures• Motility measures

• Morphology Measures– Record the entire cell shape at each time point.

• Velocity Measures– Concern about the rate of displacement from one frame

to next divided by the time interval.• Diffusivity Measures– characterize the mode of motion of the corresponding

object by inspection of the resulting Mean squared displacement time curve

• Motility Measures– track objects from measured coordinates by linear

interpolation resulting in piecewise-linear trajectories

Evaluation of techniques and its

methods• Applications and Realistic Tasks• Application Specific Metrics• Collections of Images and Ground Truth• Organizational Resources and Participants

Some applications of Bio image processing

• High-content analysis of cellular phenotypes– To determine gene functions, delineating cellular pathways, drug

discovery and even cancer diagnosis• Understanding the dynamic processes in cells and living

organisms– By imaging the distal ends of microtubules, it is made achievable to

analyze the each different dynamic patterns of microtubules in different conditions

• Reconstruction of 3D neuronal structures and the wiring diagram of a brain– Tracing and reconstruction of 3D structures of neurons is based on

automated approaches were developed recently

Conclusion

Thank you