EARDS: EfficientNet and attention-based residual depth-wise separable convolution for joint OD and OC segmentation

• Published in: Frontiers in neuroscience Vol. 17; p. 1139181
• Main Authors: Zhou, Wei, Ji, Jianhang, Jiang, Yan, Wang, Jing, Qi, Qi, Yi, Yugen
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 09.03.2023; Frontiers Media S.A
• Subjects: Accuracy; attention; Blood vessels; Classification; Computer applications; Deep learning; EfficientNet; Glaucoma; joint optic disc and cup segmentation; Machine learning; Neuroscience; residual depth-wise separable convolution; Sampling techniques; Segmentation; joint optic disc and cup segmentation; EfficientNet; attention; glaucoma; residual depth-wise separable convolution

Glaucoma is the leading cause of irreversible vision loss. Accurate Optic Disc (OD) and Optic Cup (OC) segmentation is beneficial for glaucoma diagnosis. In recent years, deep learning has achieved remarkable performance in OD and OC segmentation. However, OC segmentation is more challenging than OD...