Guided M-Net for High-Resolution Biomedical Image Segmentation with Weak Boundaries

Shihao Zhang, Yuguang Yan, Pengshuai Yin, Zhen Qiu, Wei Zhao, Guiping Cao, Wan Chen, Jin Yuan, Risa Higashita, Qingyao Wu, Mingkui Tan, Jiang Liu

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

4 Citations (Scopus)

Abstract

Biomedical image segmentation plays an important role in automatic disease diagnosis. However, some particular biomedical images have blurred object boundaries, and may contain noises due to the limited performance of imaging device. This issue will highly affects segmentation performance, and will become even severer when images have to be resized to lower resolution on a machine with limited memory. To address this, we propose a guide-based model, called G-MNet, which seeks to exploit edge information from guided map to guide the corresponding lower resolution outputs. The guided map is generated from multi-scale input to provide a better guidance. In these ways, the segmentation model will be more robust to noises and blurred object boundaries. Extensive experiments on two biomedical image datasets demonstrate the effectiveness of the proposed method.

Original languageEnglish
Title of host publicationOphthalmic Medical Image Analysis - 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Proceedings
EditorsHuazhu Fu, Mona K. Garvin, Tom MacGillivray, Yanwu Xu, Yalin Zheng
PublisherSpringer
Pages43-51
Number of pages9
ISBN (Print)9783030329556
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2019, held in conjunction with the 22nd International Conference on Medical Imaging Computing and Computer-Assisted Intervention, MICCAI 2019 - Shenzhen, China
Duration: 17 Oct 201917 Oct 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11855 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2019, held in conjunction with the 22nd International Conference on Medical Imaging Computing and Computer-Assisted Intervention, MICCAI 2019
Country/TerritoryChina
CityShenzhen
Period17/10/1917/10/19

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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