Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem

Jun Yi Wang; Michael M. Ngo; David Hessl; Randi J. Hagerman; Susan M. Rivera

doi:10.1371/journal.pone.0156123

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Peer-reviewed

Research Article

Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem

Jun Yi Wang,

Affiliation Center for Mind and Brain, University of California-Davis, Davis, California, United States of America
⨯
Michael M. Ngo,

Affiliation Center for Mind and Brain, University of California-Davis, Davis, California, United States of America
⨯
David Hessl,

Affiliations Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, University of California-Davis Medical Center, Sacramento, California, United States of America, Department of Psychiatry and Behavioral Sciences, University of California-Davis, School of Medicine, Sacramento, California, United States of America
⨯
Randi J. Hagerman,

Affiliations Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, University of California-Davis Medical Center, Sacramento, California, United States of America, Department of Pediatrics, University of California-Davis, School of Medicine, Sacramento, California, United States of America
⨯
Susan M. Rivera

* E-mail: srivera@ucdavis.edu

Current address: Center for Mind and Brain, 267 Cousteau Place, Davis, California 95618, United States of America

Affiliations Center for Mind and Brain, University of California-Davis, Davis, California, United States of America, Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, University of California-Davis Medical Center, Sacramento, California, United States of America, Department of Psychology, University of California-Davis, Davis, California, United States of America
⨯

Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem

Jun Yi Wang,
Michael M. Ngo,
David Hessl,
Randi J. Hagerman,
Susan M. Rivera

Published: May 23, 2016
https://doi.org/10.1371/journal.pone.0156123

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