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3D Segmentation in the Clinic: A Grand Challenge II: MS lesion segmentation
Departments of Psychiatry, Computer Science, Neuroradiology and Neurology, University of North Carolina at Chapel Hill, Department of Radiology, Children\'s Hospital Boston,
|Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/1509|
Submitted by Martin Styner on 11-03-2008.
This paper describes the setup of a segmentation competition for the automatic extraction of Multiple Sclerosis (MS) lesions from brain Magnetic Resonance Imaging (MRI) data. This competition is one of three competitions that make up a comparison workshop at the 2008 Medical Image Computing and Computer Assisted Intervention (MICCAI) conference and was modeled after the successful comparison workshop on liver and caudate segmentation at the 2007 MICCAI conference. In this paper, the rationale for organizing the competition is discussed, the training and test data sets for both segmentation tasks are described and the scoring system used to evaluate the segmentation is presented.
|Categories:||Classification, Segmentation, Unsupervised learning and clustering|
|Keywords:||MS lesions, Lesion segmentation, MRI, Segmentation evaluation|
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