ITK Release 4/A2D2 Projects/Comprehensive Workflow for Large Histology Segmentation and Visualization: Difference between revisions

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= Deliverables =
= Deliverables =
*New classes
* New classes
**Color correction, artifact removal, image registration
** Artifact removal
*** itk::2PointCorrelationFunctionSegmentationInitialization.h
*** itk::SupervisedBayesianClassifierFilter.h (name of developer..)
** Image registration
 
= Team =
= Team =


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

Latest revision as of 15:48, 31 August 2011

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.

Goals

Data

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