Fully automatic segmentation of multiple sclerosis lesions in brain MR FLAIR images using adaptive mixtures method and markov random field model

Computers in Biology and Medicine

Volumn 38, Issue 3, 2008, Pages 379-390

  Khayati, Rasoul ^a   Vafadust, Mansur ^a   Towhidkhah, Farzad ^a   Nabavi, Massood ^b  

^a AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

^b SHAHED UNIVERSITY   (Iran)

Author keywords

Adaptive mixtures method; Multiple sclerosis; Segmentation

Indexed keywords

BAYESIAN NETWORKS; MARKOV PROCESSES; PROBABILITY;

ADAPTIVE MIXTURES METHOD; AUTOMATIC SEGMENTATION; BAYESIAN CLASSIFIER; MARKOV RANDOM FIELD (MRF) MODEL; MULTIPLE SCLEROSIS;

IMAGE SEGMENTATION;

ADULT; ARTICLE; AUTOMATION; BRAIN DAMAGE; CLINICAL ARTICLE; FEMALE; HUMAN; IMAGE ANALYSIS; INTERMETHOD COMPARISON; MALE; MULTIPLE SCLEROSIS; NEURORADIOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PERFORMANCE; PRIORITY JOURNAL; PROBABILITY; STATISTICAL MODEL; VOLUMETRY;

ADULT; ALGORITHMS; BAYES THEOREM; FALSE NEGATIVE REACTIONS; FALSE POSITIVE REACTIONS; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; MARKOV CHAINS; MODELS, STATISTICAL; MULTIPLE SCLEROSIS; PROBABILITY; REPRODUCIBILITY OF RESULTS;

EID: 39549119121     PISSN: 00104825     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2007.12.005     Document Type: Article

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