Automatic feature learning to grade nuclear cataracts based on deep learning

IEEE Transactions on Biomedical Engineering

Volumn 62, Issue 11, 2015, Pages 2693-2701

  Gao, Xinting ^a   Lin, Stephen ^b   Wong, Tien Yin ^c  

^a INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

^b MICROSOFT RESEARCH ASIA   (China)

^c SINGAPORE EYE RESEARCH INSTITUTE   (Singapore)

Author keywords

Automatic Feature Learning; Cataract Grading; Deep Learning

Indexed keywords

DIAGNOSIS; ERRORS; IMAGE ACQUISITION; NEURAL NETWORKS;

CLINICAL MANAGEMENT; CLINICAL RESEARCH; CONVOLUTIONAL NEURAL NETWORK; DEEP LEARNING; FEATURE LEARNING; MEAN ABSOLUTE ERROR; RECURSIVE NEURAL NETWORKS; SUPPORT VECTOR REGRESSION (SVR);

GRADING;

ALGORITHM; ANATOMICAL CONCEPTS; ARTICLE; BIOMICROSCOPY; CATARACT; CONVOLUTIONAL RECURSIVE NEURAL NETWORK; DISEASE CLASSIFICATION; DISEASE SEVERITY; DISEASE SEVERITY ASSESSMENT; HUMAN; IMAGE PROCESSING; INFORMATION PROCESSING; MACHINE LEARNING; OPTICAL COHERENCE TOMOGRAPHY; SUPPORT VECTOR MACHINE; ADULT; ARTIFICIAL NEURAL NETWORK; CLASSIFICATION; LENS; PATHOLOGY; VISUAL SYSTEM EXAMINATION;

ADULT; ALGORITHMS; CATARACT; DIAGNOSTIC TECHNIQUES, OPHTHALMOLOGICAL; HUMANS; LENS, CRYSTALLINE; NEURAL NETWORKS (COMPUTER);

EID: 84946714467     PISSN: 00189294     EISSN: 15582531     Source Type: Journal    
DOI: 10.1109/TBME.2015.2444389     Document Type: Article

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