期刊
IEEE ACCESS
卷 5, 期 -, 页码 17077-17088出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2017.2740239
关键词
Computer aided diagnosis; retinal; exudates; superpixel; multi-feature classification
资金
- National Natural Science Foundation of China [61602222, 41661083, 61471110, 61602221, 71762018, 61701101]
- Foundation of Liaoning Educational Department [L2014090]
- Fundamental Research Fund for the Central Universities of China [N140403005, N150403009, N162610004]
- Doctoral Fund of Jiangxi Normal University [7525]
- Science and Technology Research Project of Jiangxi Provincial Department of Education [GJJ160333]
- Natural Science Foundation of Jiangxi Province [20171BAB212009]
Exudates can be regarded as one of the most prevalent clinical signs of diabetic retinopathy, and the detection of exudates has important clinical significance in diabetic retinopathy diagnosis. In this paper, a novel approach named superpixel multi-feature classification for the automatic detection of exudates is developed. First, an entire image is segmented into a series of superpixels considered as candidates. Then, a total of 20 features, including 19 multi-channel intensity features and a novel contextual feature, are proposed for characterizing each candidate. A supervised multi-variable classification algorithm is also introduced to distinguish the true exudates from the spurious candidates. Finally, a novel optic disc detection technique is designed to further improve the performance of classification accuracy. Extensive experiments are carried out on two publicly available online databases, DiaretDB1, and e-ophtha EX. Compared with other state-of-the-art approaches, the experimental results show the advantages and effectiveness of the proposed approach.
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