Systematic assessment of performance prediction techniques in medical image classification: A case study on celiac disease

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

Volumn 6801 LNCS, Issue , 2011, Pages 498-509

  Hegenbart, Sebastian ^a   Uhl, Andreas ^a   Vécsei, Andreas ^b  

^a UNIVERSITY OF SALZBURG   (Austria)

^b ST ANNA CHILDREN S HOSPITAL   (Austria)

Author keywords

celiac disease; classification; cross validation; LOPO; over fitting

Indexed keywords

AUTOMATED CLASSIFICATION; CELIAC DISEASE; COMMON PROBLEMS; CROSS VALIDATION; CROSS-VALIDATION TECHNIQUE; DATA SETS; FEATURE DISCRIMINATION; FEATURE SUBSET SELECTION; IMAGE SETS; LEAVE-ONE-OUT CROSS VALIDATIONS; LOCAL BINARY PATTERNS; LOPO; MEDICAL IMAGE CLASSIFICATION; MEDICAL IMAGES; MULTIPLE IMAGE; OVERFITTING; PERFORMANCE PREDICTION; SUBSET SELECTION; SYSTEMATIC ASSESSMENT; TEST DATA; TRAINING DATA SETS;

DATA PROCESSING; FEATURE EXTRACTION; RATING;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; CELIAC DISEASE; COMPUTER ASSISTED DIAGNOSIS; DUODENUM; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CELIAC DISEASE; DUODENUM; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 80052336694     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-22092-0_41     Document Type: Conference Paper

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