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Digital AssetAvailable
Brain tIssue SegmentatiOn pipeliNe (BISON)
Faculty of Medicine and Health Sciences
Biomedical Engineering
McGill University
Accurate automated tissue segmentation is challenging due to the variability in the tissue intensity profiles caused by differences in scanner models, acquisition protocols, as well as the age of the subjects and presence of pathology. We have developed BISON (Brain tIssue SegmentatiOn pipeliNe), a new pipeline for tissue segmentation using a random forests classifier and a set of intensity and location priors obtained based on T1w images.
NIST Lab
Faculty of Medicine and Health Sciences
Research lab focused on advancing scientific knowledge and innovation.
LC
Louis Collins
Digital AssetAvailable
Brain tIssue SegmentatiOn pipeliNe (BISON)
Faculty of Medicine and Health Sciences
Biomedical Engineering
McGill University
Accurate automated tissue segmentation is challenging due to the variability in the tissue intensity profiles caused by differences in scanner models, acquisition protocols, as well as the age of the subjects and presence of pathology. We have developed BISON (Brain tIssue SegmentatiOn pipeliNe), a new pipeline for tissue segmentation using a random forests classifier and a set of intensity and location priors obtained based on T1w images.
NIST Lab
Faculty of Medicine and Health Sciences
Research lab focused on advancing scientific knowledge and innovation.
LC
Louis Collins
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