Exploiting ensemble learning for automatic cataract detection and grading

Computer Methods and Programs in Biomedicine

Volumn 124, Issue , 2016, Pages 45-57

  Yang, Ji Jiang ^a   Li, Jianqiang ^b   Shen, Ruifang ^a   Zeng, Yang ^c   He, Jian ^b   Bi, Jing ^b   Li, Yong ^b   Zhang, Qinyan ^c   Peng, Lihui ^a   Wang, Qing ^a  

^a TSINGHUA UNIVERSITY   (China)

^b BEIJING UNIVERSITY OF TECHNOLOGY   (China)

^c BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

Author keywords

Cataract detection; Ensemble learning; Fundus image classification; Neural network; Support vector machines

Indexed keywords

BACKPROPAGATION; DIAGNOSIS; GRADING; NEURAL NETWORKS; OPHTHALMOLOGY; SUPPORT VECTOR MACHINES;

BACK PROPAGATION NEURAL NETWORKS; CLASSIFICATION RATES; DIAGNOSTIC ACCURACY; EARLY INTERVENTION; EMPIRICAL EXPERIMENTS; ENSEMBLE CLASSIFIERS; ENSEMBLE LEARNING; HEALTH CARE PROFESSIONALS;

IMAGE CLASSIFICATION;

ARTICLE; BACK PROPAGATION; BACK PROPAGATION NEURAL NETWORK; CATARACT; CLASSIFIER; DIAGNOSTIC ACCURACY; DISEASE SEVERITY; ENSEMBLE LEARNING; HUMAN; INVESTIGATIVE PROCEDURES; LEARNING; RETINA IMAGE; SUPPORT VECTOR MACHINE; TASK PERFORMANCE; ALGORITHM; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; IMAGE ENHANCEMENT; MACHINE LEARNING; OPHTHALMOSCOPY; PATHOLOGY; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; CATARACT; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MACHINE LEARNING; OPHTHALMOSCOPY; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84954477099     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2015.10.007     Document Type: Article

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