Lightweight pyramid network with spatial attention mechanism for accurate retinal vessel segmentation.

Journal: International journal of computer assisted radiology and surgery
Published Date:

Abstract

PURPOSE: The morphological characteristics of retinal vessels are vital for the early diagnosis of pathological diseases such as diabetes and hypertension. However, the low contrast and complex morphology pose a challenge to automatic retinal vessel segmentation. To extract precise semantic features, more convolution and pooling operations are adopted, but some structural information is potentially ignored.

Authors

  • Tengfei Tan
    University of Science and Technology of China, No.96, JinZhai Road Baohe District, Hefei, 230026, Anhui, People's Republic of China.
  • Zhilun Wang
    University of Science and Technology of China, No.96, JinZhai Road Baohe District,Hefei, Anhui 230026, PR China.
  • Hongwei Du
    Center for Biomedical Imaging, University of Science and Technology of China, Hefei, Anhui, China. Electronic address: duhw@ustc.edu.cn.
  • Jinzhang Xu
    School of Electrical Engineering and Automation, Hefei University of Technology, Hefei, Anhui 230009, China.
  • Bensheng Qiu
    Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui 230027, China.