Automatic Brain Tissue Segmentation of Multi-sequence MR Images Using Random Decision Forests
Pereira, Sérgio, Festa, Joana, Mariz, José António, Sousa, Nuno, Silva, Carlos A.
University of Minho
Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/3444
New: Prefer using the following doi: https://doi.org/10.54294/azta8g
Published in The MIDAS Journal - MICCAI 2013 Workshop: The MICCAI Grand Challenge on MR Brain Image Segmentation (MRBrainS13) .
Submitted by Sérgio Pereira on 2013-10-23 10:53:23.
This work is integrated in the MICCAI Grand Challenge: MR Brain Image Segmentation 2013. It aims for the automatic segmentation of brain into Cerebrospinal fluid (CSF), Gray matter (GM) and White matter (WM). The provided dataset contains patients with white matter lesions, which makes the segmentation task more challenging. The proposed algorithm uses multi-sequence MR images to extract meaningful features and learn a Random Decision Forest that classifies each voxel of the image. The results show that it is robust to the presence of the white matter lesions, and the metrics show that the overall results are competitive.
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