Difference between revisions of "Multimodality Image Registration for TBI"

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* Understanding brain injury using (multimodal) deformable image registration
 
* Understanding brain injury using (multimodal) deformable image registration
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* Robust registrations inspirit of topological changes (enforcing zero flow?)
+
* Robust registrations inspire of topological changes (enforcing zero flow?)
 
* CUDA-based implementation, which takes 1 min for 256x256x60
 
* CUDA-based implementation, which takes 1 min for 256x256x60
  

Revision as of 16:47, 20 June 2011

Home < Multimodality Image Registration for TBI

Multimodality 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?)
  • CUDA-based implementation, which takes 1 min for 256x256x60


Approach, Plan

  • Integration into Slicer3 Module
  • Consolidate and streamline workflow
  • Validate algorithm on various datasets

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

  1. NITRIC distribution
  2. Slicer Module
    1. Built-in: NO
    2. Extension -- commandline: NO
    3. Extension -- loadable: NO
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