Projects:NonRigidEPIRegistration
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Objective: Identify optimal ITK method and parameter settings for non-rigid intrasubject registration of T2 EPI, the raw building block images of DTI, to T1 conventional images. Provide software devliverable.
Background The registration project aims to leverage one of the general deformable registration algorithms available in ITK for use in developing a specific method to achieve intra-subject, multi-modality (EPI to T1) registration that's demonstrably better than that produced by affine tools (FLIRT, Slicer). We've developed a working tool based on ITK's BSpline method with results that are promising based on visual inspection, and identified some needed fixes (e.g. for partial brain registrations). We have a couple of several-subject datasets with DTI and MPRAGE acquisitions for each subject at two separate time points. We've initiated a study to assess robustness of affine registrations of DTI->MPRAGE and compare to robustness of our BSpline tool. This will also help drive the fixing/optimization of our tool.
Progress: We have developed the requirements specification, and created the Wiki project page and NAMIC sandbox. Test images have been identified and transfered from the 6 healthy individuals from the Dartmouth data set. We have implemented an initial rigid registration method, for comparison purposes. We also implemented the deformable registration method. Current efforts are underway to write the requsit test engine and develop the evaluation strategy.
Key Investigators:
- Kitware: Luis Ibanez
- Harvard/MGH: Dave Tuch, Denis Jen, Josh Snyder
- Dartmouth: Andrew Saykin
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