A multiple-instance learning framework for diabetic retinopathy screening

Medical Image Analysis

Volumn 16, Issue 6, 2012, Pages 1228-1240

  Quellec, Gwénolé ^a   Lamard, Mathieu ^a,b   Abràmoff, Michael D ^c   Decencière, Etienne ^d   Lay, Bruno ^e   Erginay, Ali ^f   Cochener, Béatrice ^a,b,g   Cazuguel, Guy ^a,h  

^a INSERM   (France)

^b UNIVERSITÉ DE BRETAGNE OCCIDENTALE   (France)

^c UNIVERSITY OF IOWA   (United States)

^d PSL RESEARCH UNIVERSITY   (France)

^e ADCIS   (France)

^f HÔPITAL LARIBOISIÈRE   (France)

^g BREST UNIVERSITY HOSPITAL   (France)

^h ECOLE DES MINES DE NANTES   (France)

Author keywords

Diabetic retinopathy; Lesion detection; Multiple instance learning; Pathology screening

Indexed keywords

DATA SETS; DIABETIC RETINOPATHY; DIABETIC RETINOPATHY SCREENING; IMAGE CLASSIFIERS; LARGE IMAGES; LESION DETECTION; MANUAL SEGMENTATION; MULTIPLE-INSTANCE LEARNING; REFERENCE IMAGE; RETINAL IMAGE; SEGMENTED IMAGES; SIMILAR PATTERN;

COMPUTER VISION; MEDICAL IMAGING;

EYE PROTECTION;

ARTICLE; CLINICAL FEATURE; DATA BASE; DIABETIC RETINOPATHY; EYE PHOTOGRAPHY; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; MEDICAL RECORD; MULTIPLE INSTANCE LEARNING FRAMEWORK; OPHTHALMOLOGIST; PATIENT REFERRAL; PHYSICIAN; PRIORITY JOURNAL; RETINOGRAPHY; SCORING SYSTEM;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DIABETIC RETINOPATHY; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MASS SCREENING; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; RETINOSCOPY; SENSITIVITY AND SPECIFICITY;

EID: 84866110731     PISSN: 13618415     EISSN: 13618423     Source Type: Journal    
DOI: 10.1016/j.media.2012.06.003     Document Type: Article

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