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Unsupervised MR harmonization by learning disentangled representations using information bottleneck theory.
Zuo, Lianrui; Dewey, Blake E; Liu, Yihao; He, Yufan; Newsome, Scott D; Mowry, Ellen M; Resnick, Susan M; Prince, Jerry L; Carass, Aaron.
Affiliation
  • Zuo L; Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218 USA; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institute of Health, Baltimore, MD 20892, USA. Electronic address: lr_zuo@jhu.edu.
  • Dewey BE; Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218 USA.
  • Liu Y; Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218 USA.
  • He Y; Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218 USA.
  • Newsome SD; Department of Neurology, The Johns Hopkins School of Medicine, Baltimore, MD 21287, USA.
  • Mowry EM; Department of Neurology, The Johns Hopkins School of Medicine, Baltimore, MD 21287, USA.
  • Resnick SM; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institute of Health, Baltimore, MD 20892, USA.
  • Prince JL; Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218 USA.
  • Carass A; Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218 USA.
Neuroimage ; 243: 118569, 2021 11.
Article in En | MEDLINE | ID: mdl-34506916
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Magnetic Resonance Imaging Limits: Humans Language: En Journal: Neuroimage Journal subject: DIAGNOSTICO POR IMAGEM Year: 2021 Type: Article
Fulltext
Print
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PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Magnetic Resonance Imaging Limits: Humans Language: En Journal: Neuroimage Journal subject: DIAGNOSTICO POR IMAGEM Year: 2021 Type: Article