Difference between revisions of "2009 UNC HAMMER WML"

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Design ITK classes for Hierarchical Attribute Matching Mechanism for Elastic Registration (HAMMER) and White Matter Lesion segmentation so that these algorithms can be easily implemented using the Insight Toolkit and integrated into Slicer. The goals of the week is to analyze the algorithms on the object level, map components to existing ITK classes, identify gaps, and start implementation. Will also identify testing dataset and generate ground truth for future test.  
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Design ITK classes for Hierarchical Attribute Matching Mechanism for Elastic Registration (HAMMER) and White Matter Lesion segmentation so that these algorithms can be easily implemented using the Insight Toolkit and integrated into Slicer. The goals of the week is to analyze the algorithms on the object level, map components to existing ITK classes, identify gaps, and start implementation. Will also identify testing dataset and generate baseline results for testing.  
 
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Revision as of 15:17, 7 January 2009

Home < 2009 UNC HAMMER WML
Deformable registration using HAMMER (Heirarchical Attribute Matching Mechanism for Elastic Registration)

Key Investigators

  • UNC: Dinggang Shen
  • GE Research: Xiaodong Tao, Jim Miller
  • UPenn: Christos Davatzikos (Consultant)


Objective

Design ITK classes for Hierarchical Attribute Matching Mechanism for Elastic Registration (HAMMER) and White Matter Lesion segmentation so that these algorithms can be easily implemented using the Insight Toolkit and integrated into Slicer. The goals of the week is to analyze the algorithms on the object level, map components to existing ITK classes, identify gaps, and start implementation. Will also identify testing dataset and generate baseline results for testing.

Approach, Plan

Software process embraced by NA-MIC community.

Progress

Both HAMMER and WML segmentation algorithms have been distributed in binary forms for a number of years and have been used by some research groups. We will start with the algorithms in their current forms to generate ground truth on publically available datasets.


References