mlsanityData to 7 Oct 2026

U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

arXiv 2401.04722 ↗First posted 9 Jan 2024eess.IV cs.CV cs.LGcited by 412

On the map: State-space sequence models (S4, Mamba) → Mamba for medical image analysis

Abstract (arXiv)

Convolutional Neural Networks (CNNs) and Transformers have been the most popular architectures for biomedical image segmentation, but both of them have limited ability to handle long-range dependencies because of inherent locality or computational complexity. To address this challenge, we introduce U-Mamba, a general-purpose network for biomedical image segmentation. Inspired by the State Space Sequence Models (SSMs), a new family of deep sequence models known for their strong capability in handling long sequences, we design a hybrid CNN-SSM block that integrates the local feature extraction power of convolutional layers with the abilities of SSMs for capturing the long-range dependency. Moreover, U-Mamba enjoys a self-configuring mechanism, allowing it to automatically adapt to various datasets without manual intervention. We conduct extensive experiments on four diverse tasks, including the 3D abdominal organ segmentation in CT and MR images, instrument segmentation in endoscopy images, and cell segmentation in microscopy images. The results reveal that U-Mamba outperforms state-of-the-art CNN-based and Transformer-based segmentation networks across all tasks. This opens new avenues for efficient long-range dependency modeling in biomedical image analysis. The code, models, and data are publicly available at https://wanglab.ai/u-mamba.html.

Key facts. Cited by 412 papers in the map (data through 7 Oct 2026). Placed in Mamba for medical image analysis, one of 10 directions in State-space sequence models (S4, Mamba). Builds on 33 of its 48 references that are in the map. First posted on arXiv 9 Jan 2024.

Builds on

33 of 48 references.

References · 33

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  4. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  5. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  6. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  7. 2016Layer Normalizationcited by 5,579
  8. 2023Mamba: Linear-Time Sequence Modeling with Selective State Spacescited by 4,616
  9. 2016Gaussian Error Linear Units (GELUs)cited by 3,431
  10. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,210
  11. 2021Efficiently Modeling Long Sequences with Structured State Spacescited by 2,424
  12. 2021TransUNet: Transformers Make Strong Encoders for Medical Image Segmentationcited by 1,552
21 more
  1. 2016Instance Normalization: The Missing Ingredient for Fast Stylizationcited by 1,187
  2. 2021UNETR: Transformers for 3D Medical Image Segmentationcited by 954
  3. 2022Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Imagescited by 823
  4. 2020Long Range Arena: A Benchmark for Efficient Transformerscited by 696
  5. 2020Image Segmentation Using Deep Learning: A Surveycited by 659
  6. 2021Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layerscited by 607
  7. 2020HiPPO: Recurrent Memory with Optimal Polynomial Projectionscited by 600
  8. 2022TotalSegmentator: robust segmentation of 104 anatomical structures in CT imagescited by 597
  9. 2019A large annotated medical image dataset for the development and evaluation of segmentation algorithmscited by 371
  10. 2022AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentationcited by 347
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  12. 2019The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 Challengecited by 188
  13. 2021nnFormer: Interleaved Transformer for Volumetric Segmentationcited by 179
  14. 2022It's Raw! Audio Generation with State-Space Modelscited by 171
  15. 20192017 Robotic Instrument Segmentation Challengecited by 166
  16. 2022Long Movie Clip Classification with State-Space Video Modelscited by 106
  17. 2020nnU-Net for Brain Tumor Segmentationcited by 103
  18. 2023STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-trainingcited by 96
  19. 2023The Multi-modality Cell Segmentation Challenge: Towards Universal Solutionscited by 39
  20. 20233D TransUNet: Advancing Medical Image Segmentation through Vision Transformerscited by 20
  21. 2021Cutting-edge 3D Medical Image Segmentation Methods in 2020: Are Happy Families All Alike?cited by 7

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 203; 2025: 128; 2026: 81.

412 papers.

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  1. 2024Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Modelcited by 1,051
  2. 2024MambaIR: A Simple Baseline for Image Restoration with State-Space Modelcited by 349
  3. 2024VideoMamba: State Space Model for Efficient Video Understandingcited by 325
  4. 2024VM-UNet: Vision Mamba UNet for Medical Image Segmentationcited by 286
  5. 2024SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentationcited by 266
  6. 2024LocalMamba: Visual State Space Model with Windowed Selective Scancited by 235
  7. 2024nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentationcited by 235
  8. 2024Swin-UMamba: Mamba-based UNet with ImageNet-based pretrainingcited by 179
  9. 2024U-KAN Makes Strong Backbone for Medical Image Segmentation and Generationcited by 176
  10. 2024PointMamba: A Simple State Space Model for Point Cloud Analysiscited by 166
  11. 2024PlainMamba: Improving Non-Hierarchical Mamba in Visual Recognitioncited by 141
  12. 2024Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentationcited by 133
38 more
  1. 2024Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spacescited by 132
  2. 2024VL-Mamba: Exploring State Space Models for Multimodal Learningcited by 93
  3. 2024VmambaIR: Visual State Space Model for Image Restorationcited by 90
  4. 2024The Hidden Attention of Mamba Modelscited by 88
  5. 2024MedMamba: Vision Mamba for Medical Image Classificationcited by 86
  6. 2024Mamba-ND: Selective State Space Modeling for Multi-Dimensional Datacited by 84
  7. 2024Graph Mamba: Towards Learning on Graphs with State Space Modelscited by 84
  8. 2024ZigMa: A DiT-style Zigzag Mamba Diffusion Modelcited by 84
  9. 2024Pan-Mamba: Effective pan-sharpening with State Space Modelcited by 73
  10. 2024Sigma: Siamese Mamba Network for Multi-Modal Semantic Segmentationcited by 71
  11. 2024Fusion-Mamba for Cross-modality Object Detectioncited by 67
  12. 2024Point Cloud Mamba: Point Cloud Learning via State Space Modelcited by 66
  13. 2024TimeMachine: A Time Series is Worth 4 Mambas for Long-term Forecastingcited by 63
  14. 2024Mamba-360: Survey of State Space Models as Transformer Alternative for Long Sequence Modelling: Methods, Applications, and Challengescited by 63
  15. 2024Multi-Scale VMamba: Hierarchy in Hierarchy Visual State Space Modelcited by 62
  16. 2024MiM-ISTD: Mamba-in-Mamba for Efficient Infrared Small Target Detectioncited by 59
  17. 2024State Space Model for New-Generation Network Alternative to Transformers: A Surveycited by 59
  18. 2024Retinexmamba: Retinex-based Mamba for Low-light Image Enhancementcited by 59
  19. 2024Gamba: Marry Gaussian Splatting with Mamba for single view 3D reconstructioncited by 56
  20. 2024LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentationcited by 54
  21. 2024Vision Mamba: A Comprehensive Survey and Taxonomycited by 53
  22. 2024Vivim: a Video Vision Mamba for Medical Video Segmentationcited by 51
  23. 2024Vision-LSTM: xLSTM as Generic Vision Backbonecited by 51
  24. 2024A Survey on Visual Mambacited by 50
  25. 2024CDMamba: Incorporating Local Clues into Mamba for Remote Sensing Image Binary Change Detectioncited by 48
  26. 2024Frequency-Assisted Mamba for Remote Sensing Image Super-Resolutioncited by 47
  27. 2024Is Mamba Capable of In-Context Learning?cited by 45
  28. 2024nnMamba: 3D Biomedical Image Segmentation, Classification and Landmark Detection with State Space Modelcited by 45
  29. 2024Dual-path Mamba: Short and Long-term Bidirectional Selective Structured State Space Models for Speech Separationcited by 45
  30. 2024UltraLight VM-UNet: Parallel Vision Mamba Significantly Reduces Parameters for Skin Lesion Segmentationcited by 45
  31. 2025MambaHSI: Spatial-Spectral Mamba for Hyperspectral Image Classificationcited by 44
  32. 2024U-shaped Vision Mamba for Single Image Dehazingcited by 40
  33. 2024MambaMixer: Efficient Selective State Space Models with Dual Token and Channel Selectioncited by 40
  34. 2024Spatial-Mamba: Effective Visual State Space Models via Structure-aware State Fusioncited by 40
  35. 2024ReMamber: Referring Image Segmentation with Mamba Twistercited by 38
  36. 2024Samba: Semantic Segmentation of Remotely Sensed Images with State Space Modelcited by 37
  37. 2024SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space Modelcited by 36
  38. 2024Audio Mamba: Bidirectional State Space Model for Audio Representation Learningcited by 36

50 most cited of 412 All 412 (JSON)

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  1. 2024MambaClinix: Hierarchical Gated Convolution and Mamba-Based U-Net for Enhanced 3D Medical Image Segmentation
  2. 2025MambaVesselNet++: A Hybrid CNN-Mamba Architecture for Medical Image Segmentation
  3. 2025A Comprehensive Analysis of Mamba for 3D Volumetric Medical Image Segmentation
  4. 2025ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation
  5. 2024Attention-Mamba: A Mamba-Enhanced Multi-Scale Parallel Inference Network for Medical Image Segmentation
  6. 2024HMT-UNet: A hybird Mamba-Transformer Vision UNet for Medical Image Segmentation
  7. 2024Rotate to Scan: UNet-like Mamba with Triplet SSM Module for Medical Image Segmentation
  8. 2024Optimizing Universal Lesion Segmentation: State Space Model-Guided Hierarchical Networks with Feature Importance Adjustment