Difference between revisions of "Multimodality Image Registration for TBI"

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Image:PW-MIT2011.png|[[2011_Summer_Project_Week#Projects|Projects List]]
 
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Image::BRAINSCutFigure.png|BRAINSCut Result Example
 
Image::BRAINSCutFigure.png|BRAINSCut Result Example
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==Key Investigators==
 
==Key Investigators==
 
* Georgia Tech: Yifei Lou and Allen Tannenbaum
 
* Georgia Tech: Yifei Lou and Allen Tannenbaum
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* UCLA: Micah Chambers, Andrei Irimia
  
  
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<h3>Objective</h3>
 
<h3>Objective</h3>
  
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* Integration into Slicer3 Module
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* Understanding brain injury using (multimodal) deformable image registration
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* Consolidate and streamline workflow
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* Robust registrations inspire of topological changes (enforcing zero flow?)
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* Validate algorithm on various datasets
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* The algorithm is based on a viscous fluid model, which can handle larger deformable as compared to the B-spline type of methods
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* CUDA-based implementation, which takes 1 min for 256x256x60
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<h3>Approach, Plan</h3>
 
<h3>Approach, Plan</h3>
  
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* Integration into Slicer3 Module
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* Learn more about TBI and our data set from Micah (UCLA NA-MIC TBI DBP team member)
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* Validate algorithm on additional TBI datasets from UCLA
  
 
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<h3>Progress</h3>
 
<h3>Progress</h3>
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* Learn more about TBI and ITK/Slicer
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* Demonstrate the efficiency of my algorithm on TBI data
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* Its failure in one registration case suggests us dividing 12 modalities into 2 subgroups and co-register within group
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* plan to write a paper and integrate my algorithm into ITK/Slicer
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Latest revision as of 14:28, 24 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
  • UCLA: Micah Chambers, Andrei Irimia


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

  • Learn more about TBI and ITK/Slicer
  • Demonstrate the efficiency of my algorithm on TBI data
  • Its failure in one registration case suggests us dividing 12 modalities into 2 subgroups and co-register within group
  • plan to write a paper and integrate my algorithm into ITK/Slicer



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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