MedSegViG: Medical Image Segmentation with a Vision Graph Neural Network

Xinhong Li, Geng Chen, Yuanfeng Wu, Junqing Yang, Tao Zhou, Yi Zhou, Wentao Zhu

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

Abstract

Medical image segmentation is a crucial step toward automatic clinical diagnosis, which has received growing interest. Although some existing methods based on convolutional neural networks or transformers have achieved remarkable success in this task, they still show limitations in effectively modeling the relationships among different objects in images. In this paper, we propose a novel deep learning based model to address this issue by leveraging a vision graph neural network (ViG). Our model, MedSegViG, mainly consists of a hierarchical ViG encoder and a lightweight convolutional decoder. The hierarchical encoder extracts multi-level features from the image and captures the object relationships with graph neural networks. The lightweight decoder then fuses these features and generates the corresponding segmentation map. Extensive experiments are conducted on seven datasets for three typical medical image segmentation tasks: polyp segmentation, skin lesion segmentation, and retinal vessel segmentation. The results demonstrate the superiority of our MedSegViG over state-of-the-art models across various tasks and datasets. The code is released on https://github.com/Xinhong-Li/MedSegViG.

Original languageEnglish
Title of host publicationProceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024
EditorsMario Cannataro, Huiru Zheng, Lin Gao, Jianlin Cheng, Joao Luis de Miranda, Ester Zumpano, Xiaohua Hu, Young-Rae Cho, Taesung Park
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3408-3411
Number of pages4
ISBN (Electronic)9798350386226
DOIs
StatePublished - 2024
Event2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024 - Lisbon, Portugal
Duration: 3 Dec 20246 Dec 2024

Publication series

NameProceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

Conference

Conference2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024
Country/TerritoryPortugal
CityLisbon
Period3/12/246/12/24

Keywords

  • Encoder-Decoder
  • Graph Neural Network
  • Medical Image Segmentation

Fingerprint

Dive into the research topics of 'MedSegViG: Medical Image Segmentation with a Vision Graph Neural Network'. Together they form a unique fingerprint.

Cite this