Domain-specific image analysis for cervical neoplasia detection based on conditional random fields

IEEE Transactions on Medical Imaging

Volumn 30, Issue 3, 2011, Pages 867-878

  Park, Sun Y ^a   Sargent, Dustin ^a   Lieberman, Richard ^b   Gustafsson, Ulf ^a  

^a Science and Technology International Medical Systems   (United States)

^b UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

Author keywords

Cervical cancer; classification; clustering; conditional random field; feature detection

Indexed keywords

CERVICAL CANCERS; CLASSIFICATION; CLUSTERING; CONDITIONAL RANDOM FIELD; FEATURE DETECTION;

DEVELOPING COUNTRIES; DISEASES; ENDOSCOPY; FEATURE EXTRACTION; IMAGE ANALYSIS; IMAGE SEGMENTATION; OPTICAL PROPERTIES; TISSUE;

CLUSTER ANALYSIS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; FEMALE; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; UTERINE CERVIX TUMOR;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; UTERINE CERVICAL NEOPLASMS;

EID: 79952171050     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2011.2106796     Document Type: Article

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