Optic Disc and Cup Segmentation Based on Deep Convolutional Generative Adversarial Networks

• Published in: IEEE access Vol. 7; pp. 64483 - 64493
• Main Authors: Jiang, Yun, Tan, Ning, Peng, Tingting
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive optics; Artificial neural networks; Biomedical optical imaging; deep convolutional neural networks; Deep learning; Eye diseases; Feature extraction; Generative adversarial networks; Glaucoma; Image quality; Image restoration; Image segmentation; Information retrieval; Model accuracy; optic cup segmentation; optic disc segmentation; Optical computing; Optical fiber networks; Optical imaging

Glaucoma is a chronic eye disease that causes loss of vision and it is irreversible. Accurate segmentation of optic disc and optic cup is a basic step in screening glaucoma. The most existing deep convolutional neural network (DCNN) methods have insufficient feature information extraction, and hence...