Difference between revisions of "2010 Winter Project Week HAMMER"

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Image:PW2009-v3.png|[[2009_Summer_Project_Week#Projects|Projects List]]
 
 
Image:HammerAttribute.jpg|Components of Hammer Attribute Vectors.
 
Image:HammerAttribute.jpg|Components of Hammer Attribute Vectors.
 
Image:HammerSimilarity.png|Similarity map (middle column) computed on moving image (right) for the selected point on the fixed image (left, cross). Point indicated by a cross on the middle and right column is the point on the moving image that is the most similar to the picked point on the fixed image.
 
Image:HammerSimilarity.png|Similarity map (middle column) computed on moving image (right) for the selected point on the fixed image (left, cross). Point indicated by a cross on the middle and right column is the point on the moving image that is the most similar to the picked point on the fixed image.
 
Image: namic.png|The output deformation filed by HAMMER
 
Image: namic.png|The output deformation filed by HAMMER
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Image: hammer.png|HAMMER in Slicer3
 
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<h3>Progress</h3>
 
<h3>Progress</h3>
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Since winter project week in Utah, we have developed/implemented HAMMER registration algorithm using ITK classes. New ITK classes have been created for tasks of HAMMER. Each component has been tested. The source code is version controlled at NITRC site. The current development corresponds to the original Hammer algorithm that is based on tissue classification of T1 weighted images (as outlined on the first HAMMER paper).
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* During this past week (2010), we finalized HAMMER "alpha" release on NITRC and gave a tutorial. In the next couple of weeks, we will continue to polish the tutorial and code, provide support to and collect feedback from early HAMMER adapters.
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* Since winter project week 2009 in Utah, we have developed/implemented HAMMER registration algorithm using ITK classes. New ITK classes have been created for tasks of HAMMER. Each component has been tested. The source code is version controlled at NITRC site. The current development corresponds to the original Hammer algorithm that is based on tissue classification of T1 weighted images (as outlined on the first HAMMER paper).
  
 
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<h3>Progress in this na-mic meeting</h3>
 
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We have finished following work in this na-mic project meeting:
 
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1. Implemented the framework of multi-resolution.
 
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2. Integrated affine registration as the pre-processing step before HAMMER algorithm.
 
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3. Build up the interface for algorithm.
 
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<h3>Future plan</h3>
 
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We will continue developping and testing our project after Na-mic meeting. Below is the TO-DO list:
 
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1. Automatically performing skull striping;
 
  
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2. Integrating HAMMER algorithm as the the module in Slicer
 
  
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3. Do extensive test on the algorithm and release to the Na-mic community.
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<h3>HAMMER users (will update as the list grows):</h3>
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<h3>Users List</h3>
 
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We have released our registration method to the Na-mic society. Below is the list of users:
 
  
 
1. Minjie Wu, Geriatric Psychiatry Neuroimaging Lab, University of Pittsburgh
 
1. Minjie Wu, Geriatric Psychiatry Neuroimaging Lab, University of Pittsburgh

Latest revision as of 17:26, 8 January 2010

Home < 2010 Winter Project Week HAMMER

  • Components of Hammer Attribute Vectors.

  • Similarity map (middle column) computed on moving image (right) for the selected point on the fixed image (left, cross). Point indicated by a cross on the middle and right column is the point on the moving image that is the most similar to the picked point on the fixed image.

  • The output deformation filed by HAMMER

  • HAMMER in Slicer3

Key Investigators

  • UNC: Guorong Wu, Dinggang Shen
  • GE : Xiaodong Tao, Jim Miller

Objective

We will continue developping and testing HAMMER registration algorithm implemented using ITK. The goal is to have an initial version ready by the end of the week that can be distributed within NA-MIC community for more extensive testing.

Approach, Plan

We will develop a Slicer module for the current implementation of the Hammer registration algorithm and test on images from multiple sources to make the algorithm robust and easy to use. Base line results and test will be generated.

Progress

  • During this past week (2010), we finalized HAMMER "alpha" release on NITRC and gave a tutorial. In the next couple of weeks, we will continue to polish the tutorial and code, provide support to and collect feedback from early HAMMER adapters.
  • Since winter project week 2009 in Utah, we have developed/implemented HAMMER registration algorithm using ITK classes. New ITK classes have been created for tasks of HAMMER. Each component has been tested. The source code is version controlled at NITRC site. The current development corresponds to the original Hammer algorithm that is based on tissue classification of T1 weighted images (as outlined on the first HAMMER paper).


HAMMER users (will update as the list grows):

1. Minjie Wu, Geriatric Psychiatry Neuroimaging Lab, University of Pittsburgh

References

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