# Deep Vessel Segmentation By Learning Graphical Connectivity

arXiv: https://arxiv.org/abs/1806.02279 · HTML: https://mlsanity.com/paper/1806.02279/

## Key facts

- Cited by 43 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Jun 2018.

## Built on by (most cited first, 30 of 43)

- [Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future](https://mlsanity.com/paper/2105.13137/) (2021)
- [A Survey on Graph Neural Networks and Graph Transformers in Computer Vision: A Task-Oriented Perspective](https://mlsanity.com/paper/2209.13232/) (2022)
- [Segmentation and Vascular Vectorization for Coronary Artery by Geometry-based Cascaded Neural Network](https://mlsanity.com/paper/2305.04208/) (2023)
- [Serp-Mamba: Advancing High-Resolution Retinal Vessel Segmentation with Selective State-Space Model](https://mlsanity.com/paper/2409.04356/) (2024)
- [Retinal Vessel Segmentation via a Multi-resolution Contextual Network and Adversarial Learning](https://mlsanity.com/paper/2304.12856/) (2023)
- [Semi-Supervised Semantic Segmentation of Vessel Images using Leaking Perturbations](https://mlsanity.com/paper/2110.11998/) (2021)
- [NexToU: Efficient Topology-Aware U-Net for Medical Image Segmentation](https://mlsanity.com/paper/2305.15911/) (2023)
- [DIAS: A Dataset and Benchmark for Intracranial Artery Segmentation in DSA sequences](https://mlsanity.com/paper/2306.12153/) (2023)
- [Orientation and Context Entangled Network for Retinal Vessel Segmentation](https://mlsanity.com/paper/2207.11396/) (2022)
- [PointScatter: Point Set Representation for Tubular Structure Extraction](https://mlsanity.com/paper/2209.05774/) (2022)
- [VSR-Net: Vessel-like Structure Rehabilitation Network with Graph Clustering](https://mlsanity.com/paper/2312.13116/) (2023)
- [Single Neuron Segmentation using Graph-based Global Reasoning with Auxiliary Skeleton Loss from 3D Optical Microscope Images](https://mlsanity.com/paper/2101.08910/) (2021)
- [Graph Convolutional Networks for Multi-modality Medical Imaging: Methods, Architectures, and Clinical Applications](https://mlsanity.com/paper/2202.08916/) (2022)
- [Graph Convolution Based Cross-Network Multi-Scale Feature Fusion for Deep Vessel Segmentation](https://mlsanity.com/paper/2301.02393/) (2023)
- [Structure and position-aware graph neural network for airway labeling](https://mlsanity.com/paper/2201.04532/) (2022)
- [Robust PCA Unrolling Network for Super-resolution Vessel Extraction in X-ray Coronary Angiography](https://mlsanity.com/paper/2204.08466/) (2022)
- [Graph-based Pyramid Global Context Reasoning with a Saliency-aware Projection for COVID-19 Lung Infections Segmentation](https://mlsanity.com/paper/2103.04235/) (2021)
- [Robust Implementation of Foreground Extraction and Vessel Segmentation for X-ray Coronary Angiography Image Sequence](https://mlsanity.com/paper/2209.07237/) (2022)
- [Deep vessel segmentation based on a new combination of vesselness filters](https://mlsanity.com/paper/2402.14509/) (2024)
- [DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image](https://mlsanity.com/paper/2506.05820/) (2025)
- [RVD: A Handheld Device-Based Fundus Video Dataset for Retinal Vessel Segmentation](https://mlsanity.com/paper/2307.06577/) (2023)
- [EAR-NET: Error Attention Refining Network For Retinal Vessel Segmentation](https://mlsanity.com/paper/2107.01351/) (2021)
- [A Binary Characterization Method for Shape Convexity and Applications](https://mlsanity.com/paper/2203.11395/) (2022)
- [ELEMENT: Multi-Modal Retinal Vessel Segmentation Based on a Coupled Region Growing and Machine Learning Approach](https://mlsanity.com/paper/2605.20458/) (2026)
- [Self-Supervised Learning from Unlabeled Fundus Photographs Improves Segmentation of the Retina](https://mlsanity.com/paper/2108.02798/) (2021)
- [SPNet: A novel deep neural network for retinal vessel segmentation based on shared decoder and pyramid-like loss](https://mlsanity.com/paper/2202.09515/) (2022)
- [OCTAve: 2D en face Optical Coherence Tomography Angiography Vessel Segmentation in Weakly-Supervised Learning with Locality Augmentation](https://mlsanity.com/paper/2207.12238/) (2022)
- [SCOPE: Structural Continuity Preservation for Medical Image Segmentation](https://mlsanity.com/paper/2304.14572/) (2023)
- [Benchmarking Retinal Blood Vessel Segmentation Models for Cross-Dataset and Cross-Disease Generalization](https://mlsanity.com/paper/2406.14994/) (2024)
- [Retinal Vessel Segmentation with Deep Graph and Capsule Reasoning](https://mlsanity.com/paper/2409.11508/) (2024)

## Abstract (arXiv)

We propose a novel deep-learning-based system for vessel segmentation. Existing methods using CNNs have mostly relied on local appearances learned on the regular image grid, without considering the graphical structure of vessel shape. To address this, we incorporate a graph convolutional network into a unified CNN architecture, where the final segmentation is inferred by combining the different types of features. The proposed method can be applied to expand any type of CNN-based vessel segmentation method to enhance the performance. Experiments show that the proposed method outperforms the current state-of-the-art methods on two retinal image datasets as well as a coronary artery X-ray angiography dataset.