Improving pit-pattern classification of endoscopy images by a combination of experts

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

Volumn 5761 LNCS, Issue PART 1, 2009, Pages 247-254

  Häfner, Michael ^a   Gangl, Alfred ^a   Kwitt, Roland ^b   Uhl, Andreas ^b   Vécsei, Andreas ^c   Wrba, Friedrich ^a  

^a MEDICAL UNIVERSITY OF VIENNA   (Austria)

^b UNIVERSITY OF SALZBURG   (Austria)

^c ST ANNA CHILDREN S HOSPITAL   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION PERFORMANCE; CLASSIFIER COMBINATION; COLONIC POLYPS; COLONOSCOPY; COLORECTAL CANCER; IN-VIVO; PATTERN CLASSIFICATION; TEXTURE CHARACTERISTICS; TEXTURE IMAGE;

ENDOSCOPY; SURFACE STRUCTURE; TEXTURES;

MEDICAL COMPUTING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COLON POLYP; COLORECTAL TUMOR; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; GASTROINTESTINAL ENDOSCOPY; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; OBSERVER VARIATION; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COLONIC POLYPS; COLORECTAL NEOPLASMS; ENDOSCOPY, GASTROINTESTINAL; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; OBSERVER VARIATION; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84883834085     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04268-3_31     Document Type: Conference Paper

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