Difference between revisions of "2008 Summer Project Week:FluidMechanicsTractographyUCLA"

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We have developed and initially validated a DTI tractography method based on Navier-Stokes fluid mechanics.  See the papers listed in the reference section for complete details on the method.  Our approach for this project week will focus on the following:  
 
We have developed and initially validated a DTI tractography method based on Navier-Stokes fluid mechanics.  See the papers listed in the reference section for complete details on the method.  Our approach for this project week will focus on the following:  
 
* Building the our current CL Slicer module into an interactive GUI in Slicer 3.
 
* Building the our current CL Slicer module into an interactive GUI in Slicer 3.
* Working with the tractography group in evaluating data and validating our method.   
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* Working with the interested groups in evaluating data and validating our method.   
 
 
In addition, we hope that our introdution of this method to the NA-MIC community will promote fruitful collaborations.
 
 
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Revision as of 15:35, 23 June 2008

Home < 2008 Summer Project Week:FluidMechanicsTractographyUCLA
Corticospinal tracts segmented using our fluid mechanics based tractography method.
Full brain tracts segmented using multiple fluid sources/sinks.


Key Investigators

  • UCLA: Nathan Hageman
  • UCLA: Arthur Toga, Ph.D

Objective

Computational fluid dynamics is a rich field and its application to the analysis of diffusion tensor imaging (DTI) datasets has yielded possible applications to tractography, image registration, and white matter pathology. We are developing several useful and novel diffusion tensor imaging (DTI) analysis algorithms modeled on the principles of fluid mechanics for inclusion within the NA-MIC framework. The goal of this project is to develop these methods, make them compatible with the NA-MIC ITK-based software infrastructure (i.e. Slicer), and promote their dissemination to the scientific community.

See our Project Page for more information.

Approach, Plan

We have developed and initially validated a DTI tractography method based on Navier-Stokes fluid mechanics. See the papers listed in the reference section for complete details on the method. Our approach for this project week will focus on the following:

  • Building the our current CL Slicer module into an interactive GUI in Slicer 3.
  • Working with the interested groups in evaluating data and validating our method.

Progress

Our method is currently integrated as a CL Slicer module in a custom build of Slicer 3. The module has the following functionalities:

  • reconstruction of the diffusion tensor and computation of common DTI scalar volumes (FA, LI, RGB)
  • computation of fluid velocity vector field volume
  • reconstruction of tracts based on the above fluid velocity volume

In addition, if users prefer using their own tensor reconstruction methods, the module can be run with any arbitrary set of tensor volumes.

Current work is focusing on optimizing the code for the above modules and integrating them as full interactive GUIs in Slicer3 software environment. Specifically, we are working on the following aspects:

  • Integration of method into Slicer 3
    • Finished initial coding of method in itk
    • Continuing work on the following features:
      • Multi-Threaded Implementation
      • Fluid velocity vector field animation
      • Layout for Slicer 3 Plug-in



References

  • Hageman NS, Shattuck DW, Narr K, Toga AW (2006). A diffusion tensor imaging tractography method based on Navier-Stokes fluid mechanics. Proceedings of the 2006 IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2006), Arlington, VA, USA, 6-9 April 2006. p. 798-801
  • Hageman NS, Toga AW, Narr K, Shattuck DW (2008). A diffusion tensor imaging tractography algorithm based on Navier-Stokes fluid mechanics. IEEE Trans. in Medicial Imaging, In Submission.
  • Hamilton L, Nuechterlein K, Hageman NS, Woods R, Asarnow R, Alger J, Gaser C, Toga AW, Narr K (2008). Mean Diffusivity and Fractional Anisotropy as Indicators of Schizophrenia and Genetic Vulnerability, Neuroimage, In Submission.