Discrimination of retinal images containing bright lesions using sparse coded features and SVM

Computers in Biology and Medicine

Volumn 62, Issue , 2015, Pages 175-184

  Sidibé, Désiré ^a   Sadek, Ibrahim ^a   Mériaudeau, Fabrice ^a  

^a UNIVERSITÉ DE BOURGOGNE   (France)

Author keywords

Classification; Diabetic retinopathy; Drusen; Exudates; Sparse coding

Indexed keywords

CLASSIFICATION (OF INFORMATION); DIAGNOSIS; EYE PROTECTION; IMAGE CODING; OPHTHALMOLOGY;

BAG-OF-VISUAL-WORDS; DIABETIC RETINOPATHY; DICTIONARY LEARNING; DRUSEN; EXUDATES; PROGRESSIVE DISEASE; SCREENING PERFORMANCE; SPARSE CODING;

IMAGE CLASSIFICATION;

ANATOMICAL CONCEPTS; ARTICLE; CLINICAL CLASSIFICATION; CLINICAL FEATURE; COMPARATIVE STUDY; DRUSEN; EYE COLOR; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; LEARNING ALGORITHM; PRIORITY JOURNAL; RADIODIAGNOSIS; RADIOLOGICAL PROCEDURES; RETINA EXUDATE; RETINA IMAGE; SCREENING TEST; SENSITIVITY ANALYSIS; SENSITIVITY AND SPECIFICITY; SPARSE SIGNAL REPRESENTATION TECHNIQUE; SUPPORT VECTOR MACHINE; VISUAL DISCRIMINATION; VISUAL NERVOUS SYSTEM; DIABETIC RETINOPATHY; FACTUAL DATABASE; FEMALE; MALE; PATHOLOGY; PROCEDURES; RETINA;

DATABASES, FACTUAL; DIABETIC RETINOPATHY; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MALE; RETINA;

EID: 84928629748     PISSN: 00104825     EISSN: 18790534     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2015.04.026     Document Type: Article

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