Difference between revisions of "2012 Winter Project Week:TBIDTIAnalysis"

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<h3>Objective</h3>
 
<h3>Objective</h3>
 
In vivo neuroimaging is an increasingly relevant means for the neurological assessment of traumatic brain injury (TBI). However, standard automated image analysis methods are not sufficiently robust with respect to TBI-related changes in image contrast, brain shape, cranial fractures, white matter fiber alterations, and other signatures of head injury.  
 
In vivo neuroimaging is an increasingly relevant means for the neurological assessment of traumatic brain injury (TBI). However, standard automated image analysis methods are not sufficiently robust with respect to TBI-related changes in image contrast, brain shape, cranial fractures, white matter fiber alterations, and other signatures of head injury.  
One of the objectives of the DBP is to develop robust workflows for diffusion weighted imaging (e.g. DTI, HARDI) datasets from TBI patients, by using the NA-MIC Kit and Slicer to obtain reliable and robust metrics of white matter pathology and of white matter changes due to therapy and/or recovery.  
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One of the objectives of the [http://www.na-mic.org/pages/DBP:TBI DBP] is to develop robust workflows for diffusion weighted imaging (e.g. DTI, HARDI) datasets from TBI patients, by using the NA-MIC Kit and Slicer to obtain reliable and robust metrics of white matter pathology and of white matter changes due to therapy and/or recovery.  
 
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<h3>Approach, Plan</h3>
 
<h3>Approach, Plan</h3>
*Feasibility test on shared dataset with respect to registration:
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*Objective: pairwise DTI registration and DTI analysis on TBI dataset
**Registration between acute and chronic data, i.e. only two time points but of course some deformation due to recovery.
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**Registration between acute baseline and follow-up (only two time points with some deformation due to recovery).
**Registration to an atlas (more challenging)
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**Registration from subject to atlas (more challenging)
*Discuss with interested parties to find optimal methods to handle large deformations  
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*Discuss with interested parties to find optimal methods handling such large deformations
**Combine DTI with sMRI data
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*Perform feasibility test on [[DBP3:UCLA#Results|sample DTI dataset]]
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<h3>Progress</h3>
 
<h3>Progress</h3>
 
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*Discussion with UTAH team
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*First attempt: use of DTI-Reg to register DTI images - 2 time points between acute baseline and follow-up scan
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**ANTS used to drive the registration on skull-stripped FA images
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*Data currently being processed
  
 
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Latest revision as of 15:23, 13 January 2012

Home < 2012 Winter Project Week:TBIDTIAnalysis

Registration and analysis of white matter tract changes in TBI

Key Investigators

  • UNC: Clement Vachet, Martin Styner
  • Utah: Anuja Sharma, Marcel Prastawa, Guido Gerig
  • Kitware: Danielle Pace, Stephen Aylward
  • UCLA: Andrei Irimia, Jack van Horn

Objective

In vivo neuroimaging is an increasingly relevant means for the neurological assessment of traumatic brain injury (TBI). However, standard automated image analysis methods are not sufficiently robust with respect to TBI-related changes in image contrast, brain shape, cranial fractures, white matter fiber alterations, and other signatures of head injury. One of the objectives of the DBP is to develop robust workflows for diffusion weighted imaging (e.g. DTI, HARDI) datasets from TBI patients, by using the NA-MIC Kit and Slicer to obtain reliable and robust metrics of white matter pathology and of white matter changes due to therapy and/or recovery.

Approach, Plan

  • Objective: pairwise DTI registration and DTI analysis on TBI dataset
    • Registration between acute baseline and follow-up (only two time points with some deformation due to recovery).
    • Registration from subject to atlas (more challenging)
  • Discuss with interested parties to find optimal methods handling such large deformations
  • Perform feasibility test on sample DTI dataset


Progress

  • Discussion with UTAH team
  • First attempt: use of DTI-Reg to register DTI images - 2 time points between acute baseline and follow-up scan
    • ANTS used to drive the registration on skull-stripped FA images
  • Data currently being processed

Delivery Mechanism

This work will be delivered to the NA-MIC Kit as a Slicer extension