Joint optic disc and optic cup segmentation based on boundary prior and adversarial learning.

Journal: International journal of computer assisted radiology and surgery
Published Date: May 8, 2021

Abstract

PURPOSE: The most direct means of glaucoma screening is to use cup-to-disc ratio via colour fundus photography, the first step of which is the precise segmentation of the optic cup (OC) and optic disc (OD). In recent years, convolution neural networks (CNN) have shown outstanding performance in medical segmentation tasks. However, most CNN-based methods ignore the effect of boundary ambiguity on performance, which leads to low generalization. This paper is dedicated to solving this issue.

Authors

  • Ling Luo
    Department of Epidemiology and Medical Statistics School of Public Health, Guangdong Medical University, Dongguan, Guangdong, China.
  • Dingyu Xue
    Northeastern University, Shenyang, 110819, China. xuedingyu@mail.neu.edu.cn.
  • Feng Pan
    Department of Radiation Oncology, China-Japan Union Hospital of Jilin University, Changchun, China.
  • Xinglong Feng
    Northeastern University, Shenyang, 110819, China.

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