Bayesian scalar-on-image regression with application to association between intracranial DTI and cognitive outcomes

NeuroImage

Volumn 83, Issue , 2013, Pages 210-223

  Huang, Lei ^a   Goldsmith, Jeff ^b   Reiss, Philip T ^c,d   Reich, Daniel S ^a,e,f   Crainiceanu, Ciprian M ^a  

^a JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

^b Columbia University Mailman School of Public Health ^*  (United States)

^c NEW YORK UNIVERSITY SCHOOL OF MEDICINE   (United States)

^d NATHAN S KLINE INSTITUTE FOR PSYCHIATRIC RESEARCH   (United States)

^e NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE   (United States)

^f JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Binary Markov random field; Diffusion tensor imaging; Ising prior; Multiple sclerosis

Indexed keywords

ADULT; AGED; ARTICLE; ASSOCIATION; BAYESIAN SCALAR ON IMAGE REGRESSION METHOD; BRAIN MAPPING; COGNITION; COGNITIVE DEFECT; DIFFUSION TENSOR IMAGING; FEMALE; FRACTIONAL ANISOTROPY; HUMAN; IMAGE ANALYSIS; MAJOR CLINICAL STUDY; MALE; MULTIPLE SCLEROSIS; PREDICTION; PRIORITY JOURNAL; REGRESSION ANALYSIS; SIMULATION; VOXEL BASED MORPHOMETRY; ALGORITHM; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; BIOLOGICAL MODEL; BRAIN; COGNITION DISORDERS; COMPLICATION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; MIDDLE AGED; NERVE CELL NETWORK; PATHOLOGY; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; YOUNG ADULT;

ADULT; AGED; ALGORITHMS; BAYES THEOREM; BRAIN; COGNITION; COGNITION DISORDERS; COMPUTER SIMULATION; DIFFUSION TENSOR IMAGING; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MALE; MIDDLE AGED; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; MULTIPLE SCLEROSIS; NERVE NET; PATTERN RECOGNITION, AUTOMATED; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; YOUNG ADULT;

EID: 84880946754     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2013.06.020     Document Type: Article

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