Difference between revisions of "2008 Summer Project Week:LobeParcellation"
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|[[Image:ProjectWeek-2008.png|thumb|320px|Return to [[2008_Summer_Project_Week|Project Week Main Page]] ]] | |[[Image:ProjectWeek-2008.png|thumb|320px|Return to [[2008_Summer_Project_Week|Project Week Main Page]] ]] | ||
| − | + | |[[Image:RoiPar.PNG|thumb|320px|Lobe parcellations in a coronal slice]] | |
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===Key Investigators=== | ===Key Investigators=== | ||
| − | * BWH: Sylvain Bouix, Yogesh Rathi | + | |
| + | * BWH: Sylvain Bouix, Yogesh Rathi, Padmapriya Srinivasan | ||
| + | * SPL: Kilian Pohl | ||
| + | * Kitware: Brad Davis | ||
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<h1>Objective</h1> | <h1>Objective</h1> | ||
| − | To build | + | 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. | |
| − | |||
</div> | </div> | ||
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<h1>Progress</h1> | <h1>Progress</h1> | ||
| − | We | + | * We have been using a MATLAB(R) implementation of the atlas building algorithm to construct the atlas and fine tuning it for 10 subjects. |
| − | + | * Debugging matlab code | |
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</div> | </div> | ||
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</div> | </div> | ||
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===References=== | ===References=== | ||
Latest revision as of 14:05, 27 June 2008
Home < 2008 Summer Project Week:LobeParcellation Return to Project Week Main Page |
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.
- Debugging matlab code
References
- James Malcolm, Yogesh Rathi,and Allen Tannenbaum, "Label Space: A multi-object Shape Representation", IWCIA 2008,LNCS 4958, pp. 185-196.
- 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
