Difference between revisions of "2014 Project Week:Shape Registration and Regression"

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<h3>Progress</h3>
 
<h3>Progress</h3>
 
I spoke with several people about input/output and CLI/extension.  It seems [[2014_Project_Week:MultidimensionalDataSupport|multidimensional data ]] will be available soon as the natural output for shape matching and regression.
 
I spoke with several people about input/output and CLI/extension.  It seems [[2014_Project_Week:MultidimensionalDataSupport|multidimensional data ]] will be available soon as the natural output for shape matching and regression.
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Shape matching has been implemented and integrated in Slicer.  It requires more testing on different operating systems before being released.  There are also some licensing issues with required libraries to work out. 
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After talking with some potential users of the shape regression tool, it appears an extension might be more useful that a CLI. A prototype CLI can be implemented quickly, but I think it would be cumbersome to use and its functionality limited.
 
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We show here an example of registration between a baseline synthetic tumor and a one year follow up.  The baseline MRI with tumor outline and 3D shape are shown below, with followup tumor shape shown with transparency.
  
 
[[Image:Shape_matching_interface.png|thumb|900px|center|Initial tumor data and shape matching interface. ]]
 
[[Image:Shape_matching_interface.png|thumb|900px|center|Initial tumor data and shape matching interface. ]]

Revision as of 15:57, 10 January 2014

Home < 2014 Project Week:Shape Registration and Regression

Key Investigators

  • Utah: James Fishbaugh, Guido Gerig
  • Iowa: Hans Johnson


Project Description

Objective

Integrate shape matching and shape regression tools into Slicer as command line applications.

Approach, Plan

The first step is to integrate shape matching/registration into Slicer as a command line application. Some key issues to resolve:

  • What input parameters should be made available to user?
  • Input/Output format: Paths to data or Slicer Models?
  • Output is a time series of surfaces, which is not easily explored in Slicer. Should output be simplified? Output could be the deformed source and/or the deformation field that transforms source to target.
  • Dependencies on external libraries and licensing issues.

Progress

I spoke with several people about input/output and CLI/extension. It seems multidimensional data will be available soon as the natural output for shape matching and regression.

Shape matching has been implemented and integrated in Slicer. It requires more testing on different operating systems before being released. There are also some licensing issues with required libraries to work out.

After talking with some potential users of the shape regression tool, it appears an extension might be more useful that a CLI. A prototype CLI can be implemented quickly, but I think it would be cumbersome to use and its functionality limited.

Summary


We show here an example of registration between a baseline synthetic tumor and a one year follow up. The baseline MRI with tumor outline and 3D shape are shown below, with followup tumor shape shown with transparency.

Initial tumor data and shape matching interface.
Source shape registered to target shape.
Source shape with velocity of deformation overlaid on surface.