mlsanityData to 14 Oct 2026

MUCM-Net: A Mamba Powered UCM-Net for Skin Lesion Segmentation

arXiv 2405.15925 ↗First posted 24 May 2024eess.IV cs.CV cs.LGcited by 5

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

Abstract (arXiv)

Skin lesion segmentation is key for early skin cancer detection. Challenges in automatic segmentation from dermoscopic images include variations in color, texture, and artifacts of indistinct lesion boundaries. Deep learning methods like CNNs and U-Net have shown promise in addressing these issues. To further aid early diagnosis, especially on mobile devices with limited computing power, we present MUCM-Net. This efficient model combines Mamba State-Space Models with our UCM-Net architecture for improved feature learning and segmentation. MUCM-Net's Mamba-UCM Layer is optimized for mobile deployment, offering high accuracy with low computational needs. Tested on ISIC datasets, it outperforms other methods in accuracy and computational efficiency, making it a scalable tool for early detection in settings with limited resources. Our MUCM-Net source code is available for research and collaboration, supporting advances in mobile health diagnostics and the fight against skin cancer. In order to facilitate accessibility and further research in the field, the MUCM-Net source code is https://github.com/chunyuyuan/MUCM-Net

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Placed in Mamba for medical image analysis, one of 10 directions in State-space sequence models (S4, Mamba). Builds on 25 of its 51 references that are in the map. First posted on arXiv 24 May 2024.

Builds on

25 of 51 references.

Closest ancestors · 5

Same direction, newest first

  1. 2024UltraLight VM-UNet: Parallel Vision Mamba Significantly Reduces Parameters for Skin Lesion Segmentation29 Mar
  2. 2024VM-UNET-V2 Rethinking Vision Mamba UNet for Medical Image Segmentation14 Mar
  3. 2024LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation8 Mar
  4. 2024Semi-Mamba-UNet: Pixel-Level Contrastive and Pixel-Level Cross-Supervised Visual Mamba-based UNet for Semi-Supervised Medical Image Segmentation11 Feb
  5. 2024VM-UNet: Vision Mamba UNet for Medical Image Segmentation4 Feb

Other references · 20

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  2. 2016SGDR: Stochastic Gradient Descent with Warm Restartscited by 5,045
  3. 2023Mamba: Linear-Time Sequence Modeling with Selective State Spacescited by 4,718
  4. 2022A ConvNet for the 2020scited by 3,579
  5. 2021TransUNet: Transformers Make Strong Encoders for Medical Image Segmentationcited by 1,558
  6. 2018Attention U-Net: Learning Where to Look for the Pancreascited by 1,435
  7. 2021Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentationcited by 1,222
  8. 2024Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Modelcited by 1,056
  9. 2019Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)cited by 669
  10. 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
  11. 2021TransFuse: Fusing Transformers and CNNs for Medical Image Segmentationcited by 258
  12. 2020The Computational Limits of Deep Learningcited by 193
8 more
  1. 2022UNeXt: MLP-based Rapid Medical Image Segmentation Networkcited by 185
  2. 2022MALUNet: A Multi-Attention and Light-weight UNet for Skin Lesion Segmentationcited by 59
  3. 2024State Space Model for New-Generation Network Alternative to Transformers: A Surveycited by 59
  4. 2023EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentationcited by 53
  5. 2021A comprehensive review of Binary Neural Networkcited by 45
  6. 2017ISIC 2017 - Skin Lesion Analysis Towards Melanoma Detectioncited by 34
  7. 2018The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesionscited by 26
  8. 2023UCM-Net: A Lightweight and Efficient Solution for Skin Lesion Segmentation using MLP and CNNcited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 0; 2026: 2.

5 papers.

  1. 2024Mamba in Vision: A Comprehensive Survey of Techniques and Applicationscited by 18
  2. 2024A Comprehensive Survey of Mamba Architectures for Medical Image Analysis: Classification, Segmentation, Restoration and Beyondcited by 16
  3. 2026MambaLiteUNet: Cross-Gated Adaptive Feature Fusion for Robust Skin Lesion Segmentationcited by 4
  4. 2024Venturing into Uncharted Waters: The Navigation Compass from Transformer to Mambacited by 1
  5. 2026APRIL-MedSeg: A Modular Medical Image Segmentation Toolbox Embracing Modern Paradigmscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025UltraLBM-UNet: Ultralight Bidirectional Mamba-based Model for Skin Lesion Segmentation
  2. 2024SkinMamba: A Precision Skin Lesion Segmentation Architecture with Cross-Scale Global State Modeling and Frequency Boundary Guidance
  3. 2024MambaU-Lite: A Lightweight Model based on Mamba and Integrated Channel-Spatial Attention for Skin Lesion Segmentation
  4. 2024AC-MAMBASEG: An adaptive convolution and Mamba-based architecture for enhanced skin lesion segmentation
  5. 2025ASP-VMUNet: Atrous Shifted Parallel Vision Mamba U-Net for Skin Lesion Segmentation
  6. 2024When Mamba Meets xLSTM: An Efficient and Precise Method with the xLSTM-VMUNet Model for Skin lesion Segmentation
  7. 2025Confidence-Weighted Semi-Supervised Learning for Skin Lesion Segmentation Using Hybrid CNN-Transformer Networks
  8. 2024Optimizing Universal Lesion Segmentation: State Space Model-Guided Hierarchical Networks with Feature Importance Adjustment