Laser & Optoelectronics Progress, Volume. 60, Issue 2, 0217001(2023)
Detection of Diabetic Fundus Disease Based on Deep Learning
Diabetes would increase the risk of retinal vascular disease, and may further develop into diabetic retinopathy in severe cases. Among all pathological features of diabetic retinopathy, microaneurysms, bleeding, hard exudates, and soft exudates are usually typical. In recent years, with the development of deep learning, intelligent assisted diagnostic medicine has become a trend. The premise of intelligent aided diagnosis is that the corresponding lesion area can be extracted qualitatively and quantitatively. Therefore, a model of fundus lesion detection is proposed in this paper with cascade architecture parameter optimization, which effectively solves the multi-scale and small target problems of fundus lesions. The comprehensive test accuracy of detecting lesions on DDR dataset can reach 0.380, which is better in detection performance than the current mainstream detection network.
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Gaofeng Hou, Fengzhou Fang. Detection of Diabetic Fundus Disease Based on Deep Learning[J]. Laser & Optoelectronics Progress, 2023, 60(2): 0217001
Category: Medical Optics and Biotechnology
Received: Sep. 13, 2021
Accepted: Nov. 8, 2021
Published Online: Jan. 6, 2023
The Author Email: Fang Fengzhou (fzfang@tju.edu.cn)