Voxel-based Gaussian naïve Bayes classification of ischemic stroke lesions in individual T1-weighted MRI scans

Journal of Neuroscience Methods

Volumn 257, Issue , 2016, Pages 97-108

  Griffis, Joseph C ^a   Allendorfer, Jane B ^a   Szaflarski, Jerzy P ^a  

^a UNIVERSITY OF ALABAMA AT BIRMINGHAM   (United States)

Author keywords

Chronic stroke; Lesion symptom mapping; Na ve Bayes classification; Segmentation; Supervised learning; T1 weighted MRI

Indexed keywords

ADULT; AGED; ARTICLE; AUTOMATION; BAYES THEOREM; BRAIN ISCHEMIA; BRAIN MAPPING; CLINICAL ARTICLE; FEMALE; HUMAN; IMAGE PROCESSING; LEFT HEMISPHERE; MALE; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; STROKE PATIENT; BRAIN; CEREBROVASCULAR ACCIDENT; CHRONIC DISEASE; CLASSIFICATION; COMPUTER ASSISTED DIAGNOSIS; EVALUATION STUDY; MIDDLE AGED; PATHOLOGY; PROCEDURES; REPRODUCIBILITY; SUPERVISED MACHINE LEARNING; YOUNG ADULT;

ADULT; AGED; BAYES THEOREM; BRAIN; BRAIN ISCHEMIA; CHRONIC DISEASE; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; REPRODUCIBILITY OF RESULTS; STROKE; SUPERVISED MACHINE LEARNING; YOUNG ADULT;

EID: 84944225767     PISSN: 01650270     EISSN: 1872678X     Source Type: Journal    
DOI: 10.1016/j.jneumeth.2015.09.019     Document Type: Article

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