mlsanityData to 14 Oct 2026

ViG-UNet: Vision Graph Neural Networks for Medical Image Segmentation

arXiv 2306.04905 ↗First posted 8 Jun 2023eess.IV cs.CVcited by 3

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Abstract (arXiv)

Deep neural networks have been widely used in medical image analysis and medical image segmentation is one of the most important tasks. U-shaped neural networks with encoder-decoder are prevailing and have succeeded greatly in various segmentation tasks. While CNNs treat an image as a grid of pixels in Euclidean space and Transformers recognize an image as a sequence of patches, graph-based representation is more generalized and can construct connections for each part of an image. In this paper, we propose a novel ViG-UNet, a graph neural network-based U-shaped architecture with the encoder, the decoder, the bottleneck, and skip connections. The downsampling and upsampling modules are also carefully designed. The experimental results on ISIC 2016, ISIC 2017 and Kvasir-SEG datasets demonstrate that our proposed architecture outperforms most existing classic and state-of-the-art U-shaped networks.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 19 of its 24 references that are in the map. First posted on arXiv 8 Jun 2023.

Builds on

19 of 24 references.

References · 19

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  2. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,361
  3. 2016SGDR: Stochastic Gradient Descent with Warm Restartscited by 5,045
  4. 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,292
  5. 2016Convolutional Neural Networks on Graphs with Fast Localized Spectral Filteringcited by 2,089
  6. 2021TransUNet: Transformers Make Strong Encoders for Medical Image Segmentationcited by 1,558
  7. 2018UNet++: A Nested U-Net Architecture for Medical Image Segmentationcited by 1,525
  8. 2018Attention U-Net: Learning Where to Look for the Pancreascited by 1,435
  9. 2021Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentationcited by 1,222
  10. 2013Spectral Networks and Locally Connected Networks on Graphscited by 1,102
  11. 2019Kvasir-SEG: A Segmented Polyp Datasetcited by 589
  12. 2017Skin Lesion Analysis Toward Melanoma Detection: A Challenge at the 2017 International Symposium on Biomedical Imaging (ISBI), Hosted by the International Skin Imaging Collaboration (ISIC)cited by 549
7 more
  1. 2019DeepGCNs: Can GCNs Go as Deep as CNNs?cited by 527
  2. 2016Learning Convolutional Neural Networks for Graphscited by 314
  3. 2015Deep Convolutional Networks on Graph-Structured Datacited by 246
  4. 2016FractalNet: Ultra-Deep Neural Networks without Residualscited by 216
  5. 2016Skin Lesion Analysis toward Melanoma Detection: A Challenge at the International Symposium on Biomedical Imaging (ISBI) 2016, hosted by the International Skin Imaging Collaboration (ISIC)cited by 198
  6. 2022Vision GNN: An Image is Worth Graph of Nodescited by 186
  7. 2022UNeXt: MLP-based Rapid Medical Image Segmentation Networkcited by 185

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.

  1. 2025Multi-Scale High-Resolution Logarithmic Grapher Module for Efficient Vision GNNscited by 1
  2. 2025TransGUNet: Transformer Meets Graph-based Skip Connection for Medical Image Segmentationcited by 0
  3. 2026UHR-Net: An Uncertainty-Aware Hypergraph Refinement Network for Medical Image Segmentationcited by 0