mlsanityData to 7 Oct 2026

Continuous and complete liver vessel segmentation with graph-attention guided diffusion

arXiv 2411.00617 ↗First posted 1 Nov 2024eess.IV cs.CVcited by 1

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

Improving connectivity and completeness are the most challenging aspects of liver vessel segmentation, especially for small vessels. These challenges require both learning the continuous vessel geometry, and focusing on small vessel detection. However, current methods do not explicitly address these two aspects and cannot generalize well when constrained by inconsistent annotations. Here, we take advantage of the generalization of the diffusion model and explicitly integrate connectivity and completeness in our diffusion-based segmentation model. Specifically, we use a graph-attention module that adds knowledge about vessel geometry, and thus adds continuity. Additionally, we perform the graph-attention at multiple-scales, thus focusing on small liver vessels. Our method outperforms eight state-of-the-art medical segmentation methods on two public datasets: 3D-ircadb-01 and LiVS. Our code is available at https://github.com/ZhangXiaotong015/GATSegDiff.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 21 of its 55 references that are in the map. First posted on arXiv 1 Nov 2024.

Builds on

21 of 55 references.

Closest ancestors · 5

Same direction, newest first

  1. 2024HiDiff: Hybrid Diffusion Framework for Medical Image Segmentation3 Jul
  2. 2023Memory-Efficient 3D Denoising Diffusion Models for Medical Image Processing27 Mar
  3. 2023Diff-UNet: A Diffusion Embedded Network for Volumetric Segmentation18 Mar
  4. 2022MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic Model1 Nov
  5. 2021Diffusion Models for Implicit Image Segmentation Ensembles6 Dec

Other references · 16

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  4. 2017Graph Attention Networkscited by 8,854
  5. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  6. 2015Spatial Transformer Networkscited by 1,423
  7. 2022Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Imagescited by 823
  8. 2021How Attentive are Graph Attention Networks?cited by 818
  9. 2020Learning Continuous Image Representation with Local Implicit Image Functioncited by 550
  10. 2020clDice -- A Novel Topology-Preserving Loss Function for Tubular Structure Segmentationcited by 286
  11. 2022Towards a Guideline for Evaluation Metrics in Medical Image Segmentationcited by 58
  12. 2018Deep Vessel Segmentation By Learning Graphical Connectivitycited by 43
4 more
  1. 2023Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentationcited by 34
  2. 2022Rethinking Generalization: The Impact of Annotation Style on Medical Image Segmentationcited by 10
  3. 2021Hepatic vessel segmentation based on 3D swin-transformer with inductive biased multi-head self-attentioncited by 7
  4. 2020Graph Attention Network based Pruning for Reconstructing 3D Liver Vessel Morphology from Contrasted CT Imagescited by 5

Built on by

Cited by year

Citing papers per year: 2024: 1.

1 paper.

  1. 2024Mask Approximation Net: A Novel Diffusion Model Approach for Remote Sensing Change Captioningcited by 10

Similar, not cited

Close in wording, no citation either way

  1. 2025Top-K Maximum Intensity Projection Priors for 3D Liver Vessel Segmentation
  2. 2024vesselFM: A Foundation Model for Universal 3D Blood Vessel Segmentation
  3. 2026Unsupervised Anatomical Feature Learning via Diffusion Models: Enhanced Medical Image Segmentation with Denoising Diffusion Probabilistic Models
  4. 20263D-LLDM: Label-Guided 3D Latent Diffusion Model for Improving High-Resolution Synthetic MR Imaging in Hepatic Structure Segmentation
  5. 2025PASC-Net:Plug-and-play Shape Self-learning Convolutions Network with Hierarchical Topology Constraints for Vessel Segmentation
  6. 20243D Vessel Graph Generation Using Denoising Diffusion
  7. 2025SRMA-Mamba: Spatial Reverse Mamba Attention Network for Pathological Liver Segmentation in MRI Volumes
  8. 2024Diff4MMLiTS: Advanced Multimodal Liver Tumor Segmentation via Diffusion-Based Image Synthesis and Alignment