Efficient multilevel brain tumor segmentation with integrated bayesian model classification

IEEE Transactions on Medical Imaging

Volumn 27, Issue 5, 2008, Pages 629-640

  Corso, Jason J ^a,b,c   Sharon, Eitan ^d   Dube, Shishir ^b   El Saden, Suzie ^b   Sinha, Usha ^b   Yuille, Alan ^a,b  

^a IEEE

^b UNIVERSITY OF CALIFORNIA   (United States)

^c the State University of New York   (United States)

^d TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

Bayesian affinity; Brain tumor; Glioblastoma multiforme; Multilevel segmentation; Normalized cuts

Indexed keywords

BAYESIAN NETWORKS; BRAIN; COMPUTATIONAL EFFICIENCY; IMAGE SEGMENTATION; MAGNETIC RESONANCE; MATHEMATICAL MODELS;

BAYESIAN AFFINITY; GLIOBLASTOMA MULTIFORME; MULTILEVEL SEGMENTATION; NORMALIZED CUTS;

TUMORS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; BIOLOGICAL MODEL; BRAIN TUMOR; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; SYSTEM ANALYSIS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; BRAIN NEOPLASMS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SYSTEMS INTEGRATION;

EID: 43049179622     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2007.912817     Document Type: Article

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