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Abstract #108255 Published in IGR 23-4
Joint optic disc and cup segmentation based on elliptical-like morphological feature and spatial geometry constraint
Zhao A; Su H; She C; Huang X; Li H; Qiu H; Jiang Z; Huang GComputers in Biology and Medicine 2023; 158: 106796
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.
School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, 100081, China; Advanced Innovation Center for Intelligent Robots and Systems, Beijing, 100081, China; Key Laboratory of Biomimetic Robots and Systems of Chinese Ministry of Education, Beijing, 100081, China.
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