View source for EM Segment

==Key Investigators==
* Sylvain Jaume, MIT
* Nicolas Rannou, BWH
* Koen Van Leemput, MGH
* Polina Golland, MIT
* Steve Pieper, BWH
* Ron Kikinis, BWH

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<h3>Objective</h3>
The goal of this project is to create a segmentation module in Slicer3 that offers a high productivity and reliability to the clinician.
The primary application is the segmentation of MRI images using a probabilistic atlas.

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<h3>Approach, Plan</h3>
Our algorithm builds upon the Expectation Maximization theory and is structured to let the clinician make the most efficient use of his/her anatomical knowledge.
Because of our intuitive visualization of probabilities, the user can understand the probabilistic features of his/her data and can efficiently tune the parameters to obtain the most accurate segmentation.
To meet the time constraints of the tasks in a hospital, a main focus has been devoted to the acceleration of the EM segmentation algorithm.
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<h3>Progress</h3>
A Slicer3 module for MRI Bias Field Correction has been developed to serve as a pre-processing step for the EM segmentation and is currently tested by collaborators who study alcohol and stress interaction in primates.

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==Collaboration==
* [http://www.na-mic.org/Wiki/index.php/Projects:BayesianMRSegmentation Bayesian Segmentation of MRI Images] by Koen Van Leemput, Sylvain Jaume, Polina Golland, Steve Pieper, and Ron Kikinis.
* [http://www.na-mic.org/Wiki/index.php/Measuring_Alcohol_Stress_Interaction:Measuring_Alcohol_and_Stress_Interaction NA-MIC NCBC Collaboration: Measuring Alcohol and Stress Interaction] by Vidya Rajagopalan, Andriy Fedorov and Chris Wyatt.