Difference between revisions of "Multimodality Image Registration for TBI"
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Revision as of 17:17, 20 June 2011
Home < Multimodality Image Registration for TBIMultimodality Image Registration for Traumatic Brain Injury (TBI)
Key Investigators
- Georgia Tech: Yifei Lou and Allen Tannenbaum
- Micah Chambers: UCLA
Objective
- Understanding brain injury using (multimodal) deformable image registration
- Robust registrations inspire of topological changes (enforcing zero flow?)
- The algorithm is based on a viscous fluid model, which can handle larger deformable as compared to the B-spline type of methods
- CUDA-based implementation, which takes 1 min for 256x256x60
Approach, Plan
- Integration into Slicer3 Module
- Learn more about TBI and our data set from Micah (UCLA NA-MIC TBI DBP team member)
- Validate algorithm on additional TBI datasets from UCLA
Progress
References
1 Yifei Lou and Allen Tannenbaum. Multimodal Deformable Image Registration via the Bhattacharyya Distance. Submitted to IEEE Trans. Image Process. 2011
2 Yifei Lou, Xun Jia, Xuejun Gu and Allen Tannenbaum. A GPU-based Implementation of Multimodal Deformable Image Registration Based on Mutual Information or Bhattacharyya Distance. Insight Journal, 2011. [[1]]
Delivery Mechanism
This work will be delivered to the NAMIC Kit as a
- NITRIC distribution
- Slicer Module
- Built-in: NO
- Extension -- commandline: NO
- Extension -- loadable: NO