A Multi-branch Hybrid Transformer Network for Corneal Endothelial Cell Segmentation

Yinglin Zhang, Risa Higashita, Huazhu Fu, Yanwu Xu, Yang Zhang, Haofeng Liu, Jian Zhang, Jiang Liu

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Corneal endothelial cell segmentation plays a vital role in quantifying clinical indicators such as cell density, coefficient of variation, and hexagonality. However, the corneal endothelium’s uneven reflection and the subject’s tremor and movement cause blurred cell edges in the image, which is difficult to segment, and need more details and context information to release this problem. Due to the limited receptive field of local convolution and continuous downsampling, the existing deep learning segmentation methods cannot make full use of global context and miss many details. This paper proposes a Multi-Branch hybrid Transformer Network (MBT-Net) based on the transformer and body-edge branch. Firstly, we use the convolutional block to focus on local texture feature extraction and establish long-range dependencies over space, channel, and layer by the transformer and residual connection. Besides, we use the body-edge branch to promote local consistency and to provide edge position information. On the self-collected dataset TM-EM3000 and public Alisarine dataset, compared with other State-Of-The-Art (SOTA) methods, the proposed method achieves an improvement.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer Assisted Intervention – MICCAI 2021 - 24th International Conference, Proceedings
EditorsMarleen de Bruijne, Marleen de Bruijne, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert
PublisherSpringer Science and Business Media Deutschland GmbH
Pages99-108
Number of pages10
ISBN (Print)9783030871925
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021 - Virtual, Online
Duration: 27 Sep 20211 Oct 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12901 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021
CityVirtual, Online
Period27/09/211/10/21

Keywords

  • Corneal endothelial cell segmentation
  • Deep learning
  • Multi-branch
  • Transformer

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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