Bio image informatics
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Transcript of Bio image informatics
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