Computer-aided diabetic retinopathy detection using trace transforms on digital fundus images

Medical and Biological Engineering and Computing

Volumn 52, Issue 8, 2014, Pages 663-672

  Ganesan, Karthikeyan ^a   Martis, Roshan Joy ^a   Acharya, U Rajendra ^a,d   Chua, Chua Kuang ^a   Min, Lim Choo ^a   Ng, E Y K ^b   Laude, Augustinus ^c  

^a DEPARTMENT OF ELECTRONICS AND COMPUTER ENGINEERING   (Singapore)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^c TAN TOCK SENG HOSPITAL   (Singapore)

^d UNIVERSITY OF MALAYA   (Malaysia)

Author keywords

Classification; Diabetic retinopathy; Genetic algorithm; Trace transform; Vision modeling

Indexed keywords

CLASSIFICATION (OF INFORMATION); EYE PROTECTION; GENETIC ALGORITHMS; MEDICAL IMAGING; PATTERN RECOGNITION; SUPPORT VECTOR MACHINES;

CLASSIFICATION PARAMETERS; DIABETIC RETINOPATHY; DIGITAL FUNDUS IMAGES; PATTERN RECOGNITION TECHNIQUES; PROBABILISTIC NEURAL NETWORKS; RADIAL BASIS FUNCTION KERNELS; TRACE TRANSFORM; VISION MODEL;

DIAGNOSIS;

ADULT; ARTICLE; CLASSIFICATION ALGORITHM; COMPUTER ASSISTED DIAGNOSIS; DIABETIC RETINOPATHY; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; EYE FUNDUS; GENETIC ALGORITHM; HUMAN; IMAGE ANALYSIS; IMAGE QUALITY; PREDICTIVE VALUE; PRIORITY JOURNAL; PROBABILISTIC NEURAL NETWORK; RETINA IMAGE; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; SUPPORT VECTOR MACHINE; TRACE TRANSFORM; ARTIFICIAL NEURAL NETWORK; IMAGE PROCESSING; MIDDLE AGED; PROCEDURES; YOUNG ADULT;

ADULT; DIABETIC RETINOPATHY; DIAGNOSIS, COMPUTER-ASSISTED; FUNDUS OCULI; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MIDDLE AGED; NEURAL NETWORKS (COMPUTER); SUPPORT VECTOR MACHINES; YOUNG ADULT;

EID: 84906781636     PISSN: 01400118     EISSN: 17410444     Source Type: Journal    
DOI: 10.1007/s11517-014-1167-5     Document Type: Article

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