Glaucoma Detection with Retinal Fundus Images Using Segmentation and Classification
文献类型：期刊论文
| 作者 | Thisara Shyamalee, Dulani Meedeniya |
| 刊名 | Machine Intelligence Research
 |
| 出版日期 | 2022 |
| 卷号 | 19期号:6页码:563-580 |
| ISSN号 | 2731-538X |
| 关键词 | Attention U-Net segmentation classification Inception-v3 visual geometry group 19 (VGG19) residual neural network 50 (ResNet50) glaucoma fundus images |
| DOI | 10.1007/s11633-022-1354-z |
| 英文摘要 | Glaucoma is a prevalent cause of blindness worldwide. If not treated promptly, it can cause vision and quality of life to de- teriorate. According to statistics, glaucoma affects approximately 65 million individuals globally. Fundus image segmentation depends on the optic disc (OD) and optic cup (OC). This paper proposes a computational model to segment and classify retinal fundus images for glaucoma detection. Different data augmentation techniques were applied to prevent overfitting while employing several data pre-pro- cessing approaches to improve the image quality and achieve high accuracy. The segmentation models are based on an attention U-Net with three separate convolutional neural networks (CNNs) backbones: Inception-v3, visual geometry group 19 (VGG19), and residual neural network 50 (ResNet50). The classification models also employ a modified version of the above three CNN architectures. Using the RIM-ONE dataset, the attention U-Net with the ResNet50 model as the encoder backbone, achieved the best accuracy of 99.58% in seg- menting OD. The Inception-v3 model had the highest accuracy of 98.79% for glaucoma classification among the evaluated segmentation, followed by the modified classification architectures. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/50573]  |
| 专题 | 自动化研究所_学术期刊_International Journal of Automation and Computing |
| 作者单位 | Department of Computer Science and Engineering, University of Moratuwa, Katubedda 10400, Sri Lanka |
| 推荐引用方式 GB/T 7714 | Thisara Shyamalee, Dulani Meedeniya. Glaucoma Detection with Retinal Fundus Images Using Segmentation and Classification[J]. Machine Intelligence Research,2022,19(6):563-580. |
| APA | Thisara Shyamalee, Dulani Meedeniya.(2022).Glaucoma Detection with Retinal Fundus Images Using Segmentation and Classification.Machine Intelligence Research,19(6),563-580. |
| MLA | Thisara Shyamalee, Dulani Meedeniya."Glaucoma Detection with Retinal Fundus Images Using Segmentation and Classification".Machine Intelligence Research 19.6(2022):563-580. |
入库方式： OAI收割
来源：自动化研究所
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