Difference between revisions of "2008 Winter Project Week Template"

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|[[Image:NAMIC-SLC.jpg|thumb|320px|Return to [[2008_Winter_Project_Week]] ]]
 
|[[Image:NAMIC-SLC.jpg|thumb|320px|Return to [[2008_Winter_Project_Week]] ]]
|[[Image:genuFAp.jpg|thumb|320px|Scatter plot of the original FA data through the genu of the corpus callosum of a normal brain.]]
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|valign="top"|[[Image:Case24-coronal-tensors-edit.png |thumb|320px|The Cingulum Bundle Anchor Tract]]
|[[Image:genuFA.jpg|thumb|320px|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.]]
 
 
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__NOTOC__
 
__NOTOC__
 
===Key Investigators===
 
===Key Investigators===
* UNC: Isabelle Corouge, Casey Goodlett, Guido Gerig
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* Georgia Tech: John Melonakos, Vandana Mohan
* Utah: Tom Fletcher, Ross Whitaker
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* Kitware: Luis Ibanez
 
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* BWH: Mark Niethammer, Marek Kubicki
  
 
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<h1>Objective</h1>
 
<h1>Objective</h1>
We are developing methods for analyzing diffusion tensor data along fiber tracts. The goal is to be able to make statistical group comparisons with fiber tracts as a common reference frame for comparison.
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We have developed techniques for finding the optimal geodesic path (or anchor tract) between two regions of interest in DWMRI data.
  
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The objectives of this project are to port the Fast Sweeping and optimal geodesic path tractography code to ITK as well as the code to provide for volumetric segmentation of DW-MRI data.
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See our [[Algorithm:GATech:Finsler_Active_Contour_DWI| Project Page]] for more details.
  
 
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<div style="width: 27%; float: left; padding-right: 3%;">
 
<div style="width: 27%; float: left; padding-right: 3%;">
  
<h1>Approach, Plan</h1>
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<h1>Approach, Plan </h1>
 
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Our approach is described by the references below.  Our challenge is to build the ITK infrastructure (such as new ITK iterators) to support this algorithm. Our main purpose at the Project Week is to collaborate on new algorithms and clinical data to provide the best solutions for our DBP partners.
Our approach for analyzing diffusion tensors is summarized in the IPMI 2007 reference below.  The main challenge to this approach is <foo>.
 
 
 
Our plan for the project week is to first try out <bar>,...
 
 
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<h1>Progress</h1>
 
<h1>Progress</h1>
  
Software for the fiber tracking and statistical analysis along the tracts has been implemented. The statistical methods for diffusion tensors are implemented as ITK code as part of the [[NA-MIC/Projects/Diffusion_Image_Analysis/DTI_Software_and_Algorithm_Infrastructure|DTI Software Infrastructure]] project. The methods have been validated on a repeated scan of a healthy individual. This work has been published as a conference paper (MICCAI 2005) and a journal version (MEDIA 2006). Our recent IPMI 2007 paper includes a nonparametric regression method for analyzing data along a fiber tract.
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====June 2007 Project Week====
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During this Project Week, we did a lot of algorithmic design work, focusing on leveraging optimal or geodesic path information to provide for volumetric segmentations of fiber bundles.  Working with Marek Kubicki and the Harvard DBP, we were able to begin the process of applying our algorithm to the full cingulum bundle with new labelmaps and to a new fiber bundle - Arcuate. We have recently achieved significant results in volumetric segmentations using a locally-constrained region-based technique (see the images above).
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====Jan 2007 Project Half Week====
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We finished the itkDirectionalIterator which will be needed in the Fast Sweeping implementation.  Furthermore, we made progress in porting our Matlab code to ITK.
  
 
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===References===
 
===References===
* Fletcher, P.T., Tao, R., Jeong, W.-K., Whitaker, R.T., "A Volumetric Approach to Quantifying Region-to-Region White Matter Connectivity in Diffusion Tensor MRI," to appear Information Processing in Medical Imaging (IPMI) 2007.
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* J. Melonakos, M. Niethammer, V. Mohan, M. Kubicki, J. Miller, A. Tannenbaum. Locally-Constrained Region-Based Methods for DW-MRI Segmentation. Submitted to MMBIA 2007.
* Corouge, I., Fletcher, P.T., Joshi, S., Gilmore, J.H., and Gerig, G., "Fiber Tract-Oriented Statistics for Quantitative Diffusion Tensor MRI Analysis," Medical Image Analysis 10 (2006), 786--798.
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* V. Mohan, J. Melonakos, M. Niethammer, M. Kubicki, and A. Tannenbaum. Finsler Level Set Segmentation for Imagery in Oriented Domains. BMVC 2007.
* Corouge, I., Fletcher, P.T., Joshi, S., Gilmore J.H., and Gerig, G., Fiber Tract-Oriented Statistics for Quantitative Diffusion Tensor MRI Analysis, Lecture Notes in Computer Science LNCS, James S. Duncan and Guido Gerig, editors, Springer Verlag, Vol. 3749, Oct. 2005, pp. 131 -- 138
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* J. Melonakos, V. Mohan, M. Niethammer, K. Smith, M. Kubicki, and A. Tannenbaum. Finsler Tractography for White Matter Connectivity Analysis of the Cingulum Bundle. MICCAI 2007.
* C. Goodlett, I. Corouge, M. Jomier, and G. Gerig, A Quantitative DTI Fiber Tract Analysis Suite, The Insight Journal, vol. ISC/NAMIC/ MICCAI Workshop on Open-Source Software, 2005, Online publication: http://hdl.handle.net/1926/39 .
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* J. Melonakos, E. Pichon, S. Angenet, and A. Tannenbaum. Finsler Active Contours. IEEE Transactions on Pattern Analysis and Machine Intelligence, to appear in 2007.
 +
* E. Pichon and A. Tannenbaum. Curve segmentation using directional information, relation to pattern detection. In IEEE International Conference on Image Processing (ICIP), volume 2, pages 794-797, 2005.
 +
* E. Pichon, C-F Westin, and A. Tannenbaum. A Hamilton-Jacobi-Bellman approach to high angular resolution diffusion tractography. In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pages 180-187, 2005.

Latest revision as of 15:50, 27 November 2007

Home < 2008 Winter Project Week Template
The Cingulum Bundle Anchor Tract


Key Investigators

  • Georgia Tech: John Melonakos, Vandana Mohan
  • Kitware: Luis Ibanez
  • BWH: Mark Niethammer, Marek Kubicki

Objective

We have developed techniques for finding the optimal geodesic path (or anchor tract) between two regions of interest in DWMRI data.

The objectives of this project are to port the Fast Sweeping and optimal geodesic path tractography code to ITK as well as the code to provide for volumetric segmentation of DW-MRI data.

See our Project Page for more details.

Approach, Plan

Our approach is described by the references below. Our challenge is to build the ITK infrastructure (such as new ITK iterators) to support this algorithm. Our main purpose at the Project Week is to collaborate on new algorithms and clinical data to provide the best solutions for our DBP partners.

Progress

June 2007 Project Week

During this Project Week, we did a lot of algorithmic design work, focusing on leveraging optimal or geodesic path information to provide for volumetric segmentations of fiber bundles. Working with Marek Kubicki and the Harvard DBP, we were able to begin the process of applying our algorithm to the full cingulum bundle with new labelmaps and to a new fiber bundle - Arcuate. We have recently achieved significant results in volumetric segmentations using a locally-constrained region-based technique (see the images above).

Jan 2007 Project Half Week

We finished the itkDirectionalIterator which will be needed in the Fast Sweeping implementation. Furthermore, we made progress in porting our Matlab code to ITK.



References

  • J. Melonakos, M. Niethammer, V. Mohan, M. Kubicki, J. Miller, A. Tannenbaum. Locally-Constrained Region-Based Methods for DW-MRI Segmentation. Submitted to MMBIA 2007.
  • V. Mohan, J. Melonakos, M. Niethammer, M. Kubicki, and A. Tannenbaum. Finsler Level Set Segmentation for Imagery in Oriented Domains. BMVC 2007.
  • J. Melonakos, V. Mohan, M. Niethammer, K. Smith, M. Kubicki, and A. Tannenbaum. Finsler Tractography for White Matter Connectivity Analysis of the Cingulum Bundle. MICCAI 2007.
  • J. Melonakos, E. Pichon, S. Angenet, and A. Tannenbaum. Finsler Active Contours. IEEE Transactions on Pattern Analysis and Machine Intelligence, to appear in 2007.
  • E. Pichon and A. Tannenbaum. Curve segmentation using directional information, relation to pattern detection. In IEEE International Conference on Image Processing (ICIP), volume 2, pages 794-797, 2005.
  • E. Pichon, C-F Westin, and A. Tannenbaum. A Hamilton-Jacobi-Bellman approach to high angular resolution diffusion tractography. In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pages 180-187, 2005.