Multilevel segmentation and integrated bayesian model classification with an application to brain tumor segmentation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4191 LNCS - II, Issue , 2006, Pages 790-798

  Corso, Jason J ^a   Sharon, Eitan ^a   Yuille, Alan ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTATIONAL METHODS; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; MATHEMATICAL MODELS; TUMORS;

BAYESIAN MODEL CLASSIFICATIONS; BRAIN TUMOR; IMAGE DATA; MODEL-AWARE AFFINITIES;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; BIOLOGICAL MODEL; BRAIN TUMOR; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVALUATION; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; BRAIN NEOPLASMS; COMPUTER SIMULATION; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 33750262367     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11866763_97     Document Type: Conference Paper

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