Computer-aided diagnosis from weak supervision: A benchmarking study

Computerized Medical Imaging and Graphics

Volumn 42, Issue , 2015, Pages 44-50

  Kandemir, Melih ^a   Hamprecht, Fred A ^a  

^a UNIVERSITY OF HEIDELBERG   (Germany)

Author keywords

Cancer diagnosis; Diabetic retinopathy screening; Multiple instance learning

Indexed keywords

COMPUTER AIDED INSTRUCTION; DISEASES; EYE PROTECTION; LEARNING SYSTEMS; MEDICAL IMAGING; SUPERVISED LEARNING;

CAD APPLICATIONS; CANCER DIAGNOSIS; COMPUTER AIDED DIAGNOSIS(CAD); DIABETIC RETINOPATHY SCREENING; DIAGNOSTIC IMAGES; EXPERT ANNOTATIONS; MULTIPLE INSTANCE LEARNING; SUPERVISED MACHINE LEARNING;

COMPUTER AIDED DIAGNOSIS;

ARTICLE; CANCER DIAGNOSIS; COMPUTER ASSISTED DIAGNOSIS; DIABETIC RETINOPATHY; DIAGNOSTIC IMAGING; HISTOLOGY; IMAGE ANALYSIS; KERNEL METHOD; PRIORITY JOURNAL; QUALITY CONTROL; ALGORITHM; AUTOMATED PATTERN RECOGNITION; EVALUATION STUDY; HUMAN; IMAGE ENHANCEMENT; MICROSCOPY; NEOPLASM; PATHOLOGY; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STANDARDS; SUPERVISED MACHINE LEARNING; VALIDATION STUDY;

ALGORITHMS; BENCHMARKING; DIABETIC RETINOPATHY; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MICROSCOPY; NEOPLASMS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUPERVISED MACHINE LEARNING;

EID: 84926394401     PISSN: 08956111     EISSN: 18790771     Source Type: Journal    
DOI: 10.1016/j.compmedimag.2014.11.010     Document Type: Article

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