RMSDSC‐Net: A robust multiscale feature extraction with depthwise separable convolution network for optic disc and cup segmentation

• Published in: International journal of intelligent systems Vol. 37; no. 12; pp. 11482 - 11505
• Main Authors: Wei, Zhou, Yuhan, Peng, Jianhang, Ji, Jikun, Yang, Weiqi, Bai, Yugen, Yi, Wenle, Wang
• Format: Journal Article
• Language: English
• Published: New York John Wiley & Sons, Inc 01.12.2022
• Subjects: artificial intelligence; Computational efficiency; computer‐aided diagnosis; Computing time; Convolution; deep learning; Diagnosis; Eye diseases; Feature extraction; Glaucoma; Image segmentation; Intelligent systems; Machine learning; Medical imaging; optic disc, cup Segmentation; Performance evaluation; Robustness; Spatial data

Glaucoma is an eye disease that leads to irreversible vision loss. Accurate Optic Disc (OD) and Optic Cup (OC) segmentation can effectively facilitate ophthalmologist in glaucoma diagnosis. Recently, a series of deep learning approaches attain promising performance in OD and OC segmentation but stil...