ITK Release 4/A2D2 Projects/Comprehensive Workflow for Large Histology Segmentation and Visualization

Motivation

3D histology stacks are being increasingly used to understand gross anatomical changes and to provide valuable educational contexts. Most existing toolkits allow a 2D approach and do not meet the challenges posed by 3D histology. ITKv4 can facilitate the realization application level toolkits that will allow for a sensible registration, segmentation and reconstruction of digital slides depicting various organs and tissue systems. We will leverage our extensive experience in constructing ITK-based tools to process 3D histology. Modules will be included that will allow for pre-processing (color correction, artifact removal, etc.), rigid and non-rigid registration, material-based segmentation, and visualization. Additionally, we will provide access to multi resolution data that describes ensembles of nephrons in a human kidney. Our team includes an anatomist who will provide validation data and will deploy the tool in her anatomy classes. Thus, our proposed tool will bring a valuable user community into the ITK fold.

Deliverables

• New classes
  • Artifact removal
    • itk::2PointCorrelationFunctionSegmentationInitialization.h
    • itk::SupervisedBayesianClassifierFilter.h (name of developer..)
  • Image registration

Team

• Raghu Machiraju
• Kun Huang
• Lisa Lee
• Hao Ding
• Arindam Bhattacharya