mlsanityData to 13 Oct 2026

CS2-Net: Deep Learning Segmentation of Curvilinear Structures in Medical Imaging

arXiv 2010.07486 ↗First posted 15 Oct 2020eess.IV cs.CVcited by 53

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Abstract (arXiv)

Automated detection of curvilinear structures, e.g., blood vessels or nerve fibres, from medical and biomedical images is a crucial early step in automatic image interpretation associated to the management of many diseases. Precise measurement of the morphological changes of these curvilinear organ structures informs clinicians for understanding the mechanism, diagnosis, and treatment of e.g. cardiovascular, kidney, eye, lung, and neurological conditions. In this work, we propose a generic and unified convolution neural network for the segmentation of curvilinear structures and illustrate in several 2D/3D medical imaging modalities. We introduce a new curvilinear structure segmentation network (CS2-Net), which includes a self-attention mechanism in the encoder and decoder to learn rich hierarchical representations of curvilinear structures. Two types of attention modules - spatial attention and channel attention - are utilized to enhance the inter-class discrimination and intra-class responsiveness, to further integrate local features with their global dependencies and normalization, adaptively. Furthermore, to facilitate the segmentation of curvilinear structures in medical images, we employ a 1x3 and a 3x1 convolutional kernel to capture boundary features. ...

Key facts. Cited by 53 papers in the map (data through 13 Oct 2026). First posted on arXiv 15 Oct 2020.

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Citing papers per year: 2021: 1; 2022: 5; 2023: 7; 2024: 12; 2025: 14; 2026: 14.

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  1. 2023Dynamic Snake Convolution based on Topological Geometric Constraints for Tubular Structure Segmentationcited by 84
  2. 2024Skeleton Recall Loss for Connectivity Conserving and Resource Efficient Segmentation of Thin Tubular Structurescited by 43
  3. 2025RUN: Reversible Unfolding Network for Concealed Object Segmentationcited by 28
  4. 2023Synthetic optical coherence tomography angiographs for detailed retinal vessel segmentation without human annotationscited by 16
  5. 2022Local Intensity Order Transformation for Robust Curvilinear Object Segmentationcited by 12
  6. 2023Is attention all you need in medical image analysis? A reviewcited by 12
  7. 2025Reversible Unfolding Network for Concealed Visual Perception with Generative Refinementcited by 11
  8. 2023DIAS: A Dataset and Benchmark for Intracranial Artery Segmentation in DSA sequencescited by 10
  9. 2022Segmentation Ability Map: Interpret deep features for medical image segmentationcited by 9
  10. 2023VSR-Net: Vessel-like Structure Rehabilitation Network with Graph Clusteringcited by 8
  11. 2024DSCA: A Digital Subtraction Angiography Sequence Dataset and Spatio-Temporal Model for Cerebral Artery Segmentationcited by 8
  12. 2024SPIRONet: Spatial-Frequency Learning and Graph-based Channel Interaction Network for Vessel Segmentationcited by 6
38 more
  1. 2022Robust PCA Unrolling Network for Super-resolution Vessel Extraction in X-ray Coronary Angiographycited by 5
  2. 2024TESL-Net: A Transformer-Enhanced CNN for Accurate Skin Lesion Segmentationcited by 4
  3. 2022Modeling and hexahedral meshing of cerebral arterial networks from centerlinescited by 3
  4. 2024Real-time guidewire tracking and segmentation in intraoperative x-raycited by 3
  5. 2025Universal Vessel Segmentation for Multi-Modality Retinal Imagescited by 3
  6. 2025A topology-preserving three-stage framework for fully-connected coronary artery extractioncited by 3
  7. 2025HarmonySeg: Tubular Structure Segmentation with Deep-Shallow Feature Fusion and Growth-Suppression Balanced Losscited by 3
  8. 2023Swin UNETR++: Advancing Transformer-Based Dense Dose Prediction Towards Fully Automated Radiation Oncology Treatmentscited by 2
  9. 2024MOSformer: Momentum encoder-based inter-slice fusion transformer for medical image segmentationcited by 2
  10. 2025UCS: A Universal Model for Curvilinear Structure Segmentationcited by 2
  11. 2026FMS2: Unified Flow Matching for Segmentation and Synthesis of Thin Structurescited by 2
  12. 2023TSI-Net: A Timing Sequence Image Segmentation Network for Intracranial Artery Segmentation in Digital Subtraction Angiographycited by 1
  13. 2024DeepBranchTracer: A Generally-Applicable Approach to Curvilinear Structure Reconstruction Using Multi-Feature Learningcited by 1
  14. 2025Synthetic Data for Blood Vessel Network Extractioncited by 1
  15. 2025A novel attention mechanism for noise-adaptive and robust segmentation of microtubules in microscopy imagescited by 1
  16. 2025Unleashing Vision Foundation Models for Coronary Artery Segmentation: Parallel ViT-CNN Encoding and Variational Fusioncited by 1
  17. 2026Topo-R1: Detecting Topological Anomalies via Vision-Language Modelscited by 1
  18. 2026CurvSegFlow: Time-Conditioned Flow Matching for Robust Segmentation of Curvilinear Structures in Noisy Biomedical Imagescited by 1
  19. 2021RA V-Net: Deep learning network for automated liver segmentationcited by 0
  20. 2022OMSN and FAROS: OCTA Microstructure Segmentation Network and Fully Annotated Retinal OCTA Segmentation Datasetcited by 0
  21. 2024Robust semi-automatic vessel tracing in the human retinal image by an instance segmentation neural networkcited by 0
  22. 2024Guidelines for Cerebrovascular Segmentation: Managing Imperfect Annotations in the context of Semi-Supervised Learningcited by 0
  23. 2024MDFI-Net: Multiscale Differential Feature Interaction Network for Accurate Retinal Vessel Segmentationcited by 0
  24. 2024Retinal Vessel Segmentation via Neuron Programmingcited by 0
  25. 2024Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correctioncited by 0
  26. 2025ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representationcited by 0
  27. 2025SWinMamba: Serpentine Window State Space Model for Vascular Segmentationcited by 0
  28. 2025PASC-Net:Plug-and-play Shape Self-learning Convolutions Network with Hierarchical Topology Constraints for Vessel Segmentationcited by 0
  29. 2025Automated Labeling of Intracranial Arteries with Uncertainty Quantification Using Deep Learningcited by 0
  30. 2025Application of a Virtual Imaging Framework for Investigating a Deep Learning-Based Reconstruction Method for 3D Quantitative Photoacoustic Computed Tomographycited by 0
  31. 2026HUR-MACL: High-Uncertainty Region-Guided Multi-Architecture Collaborative Learning for Head and Neck Multi-Organ Segmentationcited by 0
  32. 2026VFGS-Net: Frequency-Guided State-Space Learning for Topology-Preserving Retinal Vessel Segmentationcited by 0
  33. 2026Bridging the Geometry Mismatch: Frequency-Aware Anisotropic Serialization for Thin-Structure SSMscited by 0
  34. 2026Polygon-mamba: Retinal vessel segmentation using polygon scanning mamba and space-frequency collaborative attentioncited by 0
  35. 2026Gaze into the Details: Locality-Sensitive Enhancement for OCTA Retinal Vessel Segmentationcited by 0
  36. 2026MARVEL: Universal Murray's Law-informed Vessel Tree Segmentation and Topology Estimationcited by 0
  37. 2026CSWinUNETR: Segmentation of Thin Anatomical Structures in Medical Imagescited by 0
  38. 2026From Reconstruction to Decision: A Post-Encoder Plug-in Adapter for Curvilinear Segmentationcited by 0

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