Frontiers in Neuroscience (Dec 2021)

DW-Net: Dynamic Multi-Hierarchical Weighting Segmentation Network for Joint Segmentation of Retina Layers With Choroid Neovascularization

  • Lianyu Wang,
  • Meng Wang,
  • Tingting Wang,
  • Qingquan Meng,
  • Yi Zhou,
  • Yuanyuan Peng,
  • Weifang Zhu,
  • Zhongyue Chen,
  • Xinjian Chen,
  • Xinjian Chen

DOI
https://doi.org/10.3389/fnins.2021.797166
Journal volume & issue
Vol. 15

Abstract

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Choroid neovascularization (CNV) is one of the blinding factors. The early detection and quantitative measurement of CNV are crucial for the establishment of subsequent treatment. Recently, many deep learning-based methods have been proposed for CNV segmentation. However, CNV is difficult to be segmented due to the complex structure of the surrounding retina. In this paper, we propose a novel dynamic multi-hierarchical weighting segmentation network (DW-Net) for the simultaneous segmentation of retinal layers and CNV. Specifically, the proposed network is composed of a residual aggregation encoder path for the selection of informative feature, a multi-hierarchical weighting connection for the fusion of detailed information and abstract information, and a dynamic decoder path. Comprehensive experimental results show that our proposed DW-Net achieves better performance than other state-of-the-art methods.

Keywords