Fiber tractography using machine learning
Fiber tractography using machine learning
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Publisher
United States: Elsevier Inc
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Language
English
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Publisher
United States: Elsevier Inc
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Contents
We present a fiber tractography approach based on a random forest classification and voting process, guiding each step of the streamline progression by directly processing raw diffusion-weighted signal intensities. For comparison to the state-of-the-art, i.e. tractography pipelines that rely on mathematical modeling, we performed a quantitative and...
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Full title
Fiber tractography using machine learning
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TN_cdi_proquest_miscellaneous_1921133145
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_1921133145
Other Identifiers
ISSN
1053-8119
E-ISSN
1095-9572
DOI
10.1016/j.neuroimage.2017.07.028
