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Automated Walks using Machine Learning for Segmentation

Vyas, Saurabh, Burlina, Philippe, Kleissas, Dean, Mukherjee, Ryan
Johns Hopkins University
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Published in The MIDAS Journal - MICCAI 2013 Workshop: The MICCAI Grand Challenge on MR Brain Image Segmentation (MRBrainS13) .
Submitted by Saurabh Vyas on 2013-10-21 12:45:48.

This paper describes an automated algorithm for segmentation of brain structures (CSF, white matter, and gray matter) in MR images. We employ machine learning, i.e. k-Nearest Neighbors, of features derived from k-means, Canny edge detection, and Tourist Walks to fully automate the seeding process of the Random Walker algorithm. We test our methods on a dataset of 12 diabetes patients with atrophy and varying degrees of white matter lesions provided by the MRBrainS13 Challenge, and find encouraging segmentation performance.