Detection of Glaucoma in Retinal Fundus Images Using Fast Fuzzy C means clustering approach
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx7/8966553/8974457/08974539.pdf?arnumber=8974539
Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. DTN-MTLF: A dual-teacher network based multi-task learning framework for unbiased glaucoma diagnosis;Multimedia Tools and Applications;2024-04-20
2. Voxel representation of brain images inpainting via Regional Pixel Semantic Network and pyramidal attention AE - Quantile differential mechanism model;Computers in Biology and Medicine;2024-03
3. U-Net Architecture for Detecting Glaucoma with Retinal Fundus Images;2023 First International Conference on Advances in Electrical, Electronics and Computational Intelligence (ICAEECI);2023-10-19
4. Evaluation of Cup to Disc Ratio for Glaucoma detection through Optic Cup and Disc Segmentation using K-means Clustering with Morphological Operations and comparing with Adaptive Thresholding method;2022 14th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS);2022-11-12
5. Evaluation of Cup to Disc Ratio for Glaucoma detection through optic cup and disc segmentation using Fuzzy C-means clustering and comparing with adaptive thresholding method;2022 14th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS);2022-11-12
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