2010 Winter Project Week HAMMER

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  Components of Hammer Attribute Vectors.

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  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.

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  The output deformation filed by HAMMER

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

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).

Users List

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

References

• Dinggang Shen, Christos Davatzikos, HAMMER: Hierarchical Attribute Matching Mechanism for Elastic Registration, IEEE Trans. on Medical Imaging, 21(11):1421-1439, Nov 2002.