Joint optic disc and cup segmentation based on elliptical-like morphological feature and spatial geometry constraint. (May 2023)

• Record Type: Journal Article
• Authors: Zhao, Aidi; Su, Hong; She, Chongyang; Huang, Xiao; Li, Hui; Qiu, Huaiyu; Jiang, Zhihong; Huang, Gao
• Is Part Of: Computers in biology and medicine. Volume 158(2023)
• Publication Date: 2023-05
• Subjects: Deep learning -- Optic disc and cup segmentation -- Ellipse detection -- Glaucoma screening -- Spatial geometry constraint; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2023.106796
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: Glaucoma is a chronic degenerative disease that is the second leading cause of irreversible blindness worldwide. For a precise and automatic screening of glaucoma, detecting the optic disc and cup precisely is significant. In this paper, combining the elliptical-like morphological features of the disc and cup, we reformulate the segmentation task from a perspective of ellipse detection to explicitly segment and directly get the glaucoma screening indicator. We detect the minimum bounding boxes of ellipses firstly, and then learn the ellipse parameters of these regions to achieve optic disc and cup segmentation. Considering the spatial geometry prior knowledge that the cup should be within the disc region, Paired-Box RPN is introduced to simultaneously detect the disc and cup coupled. In addition, boundary attention module is introduced to use edges of the disc and cup as an important guide for context aggregation to improve the accuracy. Comprehensive experiments clearly show that our method outperforms the state-of-the-art methods for optic disc and cup segmentation. Simultaneously, the proposed method also obtains the good glaucoma screening performance with calculated vCDR value. Joint optic disc and cup segmentation, which utilizes the elliptical-like morphological features and spatial geometry constraint, could improve the performance of optic disc and cup segmentation. Highlights: Combining elliptical-like morphological features, we explicitly segment and directly get the glaucoma screening indicator. The PB-RPN is proposed to detect the disc and cup simultaneously with spatial geometry constraint. The BAM is introduced to extract edge features to improve their discrimination.