2013 Project Week:PythonModules
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Revision as of 15:30, 3 January 2013 by Dmwelch (talk | contribs) (Created page with '__NOTOC__ <gallery> Image:PW-SLC2013.png|Projects List Image:ScarSeg_EM.png| Scar tissue identification. </gallery> ==Key Investigators=…')
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Scar tissue identification.
Key Investigators
- LiangJia Zhu, Allen Tannenbaum, UAB
- Yi Gao, BWH
- Josh Cates, Rob MacLeod, SCI
Project Description
Objective
- We are developing methods for identifying scar tissue from CARMA data. Our previous method demonstrates an effective identification ability for DE-MRI data. In this method, the intensity distribution inside the LA myocardial wall is modeled as a mixture of Gaussians. To improve the performance of this method, we will integrate the intensity information from the LA chamber into the overall identification procedure.
- We will discuss possible improvements for scar identification.
Approach, Plan
- Design an identification scheme using the LA intensity as a prior
- Test the method using CARMA data
- Deliver the implementation in CLI module.
