دورية أكاديمية
Algorithm of automatic identification of diabetic retinopathy foci based on ultra-widefield scanning laser ophthalmoscopy
العنوان: | Algorithm of automatic identification of diabetic retinopathy foci based on ultra-widefield scanning laser ophthalmoscopy |
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المؤلفون: | Jie Wang, Su-Zhen Wang, Xiao-Lin Qin, Meng Chen, Heng-Ming Zhang, Xin Liu, Meng-Jun Xiang, Jian-Bin Hu, Hai-Yu Huang, Chang-Jun Lan |
المصدر: | International Journal of Ophthalmology, Vol 17, Iss 4, Pp 610-615 (2024) |
بيانات النشر: | Press of International Journal of Ophthalmology (IJO PRESS), 2024. |
سنة النشر: | 2024 |
المجموعة: | LCC:Ophthalmology |
مصطلحات موضوعية: | diabetic retinopathy, ultra-widefield scanning laser ophthalmoscopy, intelligent diagnosis system, Ophthalmology, RE1-994 |
الوصف: | AIM: To propose an algorithm for automatic detection of diabetic retinopathy (DR) lesions based on ultra-widefield scanning laser ophthalmoscopy (SLO). METHODS: The algorithm utilized the FasterRCNN (Faster Regions with CNN features)+ResNet50 (Residua Network 50)+FPN (Feature Pyramid Networks) method for detecting hemorrhagic spots, cotton wool spots, exudates, and microaneurysms in DR ultra-widefield SLO. Subimage segmentation combined with a deeper residual network FasterRCNN+ResNet50 was employed for feature extraction to enhance intelligent learning rate. Feature fusion was carried out by the feature pyramid network FPN, which significantly improved lesion detection rates in SLO fundus images. RESULTS: By analyzing 1076 ultra-widefield SLO images provided by our hospital, with a resolution of 2600×2048 dpi, the accuracy rates for hemorrhagic spots, cotton wool spots, exudates, and microaneurysms were found to be 87.23%, 83.57%, 86.75%, and 54.94%, respectively. CONCLUSION: The proposed algorithm demonstrates intelligent detection of DR lesions in ultra-widefield SLO, providing significant advantages over traditional fundus color imaging intelligent diagnosis algorithms. |
نوع الوثيقة: | article |
وصف الملف: | electronic resource |
اللغة: | English |
تدمد: | 2222-3959 2227-4898 |
Relation: | http://ies.ijo.cn/en_publish/2024/4/20240402.pdf; https://doaj.org/toc/2222-3959; https://doaj.org/toc/2227-4898 |
DOI: | 10.18240/ijo.2024.04.02 |
URL الوصول: | https://doaj.org/article/1504080d6b054abda31aad94ee44c5bd |
رقم الأكسشن: | edsdoj.1504080d6b054abda31aad94ee44c5bd |
قاعدة البيانات: | Directory of Open Access Journals |
تدمد: | 22223959 22274898 |
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DOI: | 10.18240/ijo.2024.04.02 |