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

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===Key Investigators===
 
===Key Investigators===
* BWH: Sylvain Bouix, Yogesh Rathi
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* BWH: Sylvain Bouix, Yogesh Rathi, Padmapriya Srinivasan
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* SPL: Kilian Pohl
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* Kitware: Brad Davis
  
  
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<h1>Objective</h1>
 
<h1>Objective</h1>
To build an atlas based on 100 existing manually-lobe parcellated 1.5T data to aid in automatic lobe parcellation of 3T data.  
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To build a lobe parcellation algorithm for our 3T data set. The spatial priors are based on 100 existing manually-lobe parcellated 1.5T data.
  
  
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<h1>Approach, Plan</h1>
 
<h1>Approach, Plan</h1>
 
Our plan is to use an algorithm described in Reference 1 to construct probability maps of the lobes using an unbiased registration approach. The algorithm uses a ''label space'' representation that allows for direct registration.  
 
Our plan is to use an algorithm described in Reference 1 to construct probability maps of the lobes using an unbiased registration approach. The algorithm uses a ''label space'' representation that allows for direct registration.  
 
+
We will then tune the EMsegmenter of Slicer3 to perform the segmentation.
 
 
  
 
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<h1>Progress</h1>
 
<h1>Progress</h1>
We are using a MATLAB(R) implementation of the algorithm to construct the atlas and fine tuning it for 10 subjects.
+
We have been using a MATLAB(R) implementation of the atlas building algorithm to construct the atlas and fine tuning it for 10 subjects.  
 
 
  
 
</div>
 
</div>
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</div>
 
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===References===
 
===References===

Revision as of 14:35, 20 June 2008

Home < 2008 Summer Project Week:LobeParcellation



Key Investigators

  • BWH: Sylvain Bouix, Yogesh Rathi, Padmapriya Srinivasan
  • SPL: Kilian Pohl
  • Kitware: Brad Davis


Objective

To build a lobe parcellation algorithm for our 3T data set. The spatial priors are based on 100 existing manually-lobe parcellated 1.5T data.


Approach, Plan

Our plan is to use an algorithm described in Reference 1 to construct probability maps of the lobes using an unbiased registration approach. The algorithm uses a label space representation that allows for direct registration. We will then tune the EMsegmenter of Slicer3 to perform the segmentation.

Progress

We have been using a MATLAB(R) implementation of the atlas building algorithm to construct the atlas and fine tuning it for 10 subjects.


References

  1. James Malcolm, Yogesh Rathi,and Allen Tannenbaum, "Label Space: A multi-object Shape Representation", IWCIA 2008,LNCS 4958, pp. 185-196.
  2. Motoaki Nakamura, Dean F. Salisbury, Yoshio Hirayasu, Sylvain Bouix, Kilian M. Pohl, Takeshi Yoshida, Min-Seong Koo, Martha E. Shenton, and Robert W. McCarley, "Neocortical Gray Matter Volume in First-Episode Schizophrenia and First-Episode Affective Psychosis: A Cross-Sectional and Longitudinal MRI Study", Biol Psychiatry 2007;62:773–783