# UltraLight VM-UNet: Parallel Vision Mamba Significantly Reduces Parameters for Skin Lesion Segmentation

arXiv: https://arxiv.org/abs/2403.20035 · HTML: https://mlsanity.com/paper/2403.20035/

## Key facts

- Cited by 45 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 30 of its 47 references that are in the map.
- First posted on arXiv 29 Mar 2024.

## Placed in

- State-space sequence models (S4, Mamba) / [Mamba for medical image analysis](https://mlsanity.com/ssm/mamba-for-medical-image-analysis/)

## Builds on (most cited first, 30 of 30)

- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift](https://mlsanity.com/paper/1502.03167/) (2015)
- [Rethinking the Inception Architecture for Computer Vision](https://mlsanity.com/paper/1512.00567/) (2015)
- [Fully Convolutional Networks for Semantic Segmentation](https://mlsanity.com/paper/1411.4038/) (2014)
- [Mamba: Linear-Time Sequence Modeling with Selective State Spaces](https://mlsanity.com/paper/2312.00752/) (2023)
- [Going Deeper with Convolutions](https://mlsanity.com/paper/1409.4842/) (2014)
- [A ConvNet for the 2020s](https://mlsanity.com/paper/2201.03545/) (2022)
- [Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning](https://mlsanity.com/paper/1602.07261/) (2016)
- [Attention U-Net: Learning Where to Look for the Pancreas](https://mlsanity.com/paper/1804.03999/) (2018)
- [Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation](https://mlsanity.com/paper/2105.05537/) (2021)
- [Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model](https://mlsanity.com/paper/2401.09417/) (2024)
- [VMamba: Visual State Space Model](https://mlsanity.com/paper/2401.10166/) (2024)
- [UNETR: Transformers for 3D Medical Image Segmentation](https://mlsanity.com/paper/2103.10504/) (2021)
- [Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning](https://mlsanity.com/paper/1702.03118/) (2017)
- [Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images](https://mlsanity.com/paper/2201.01266/) (2022)
- [Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)](https://mlsanity.com/paper/1902.03368/) (2019)
- [The Medical Segmentation Decathlon](https://mlsanity.com/paper/2106.05735/) (2021)
- [Skin Lesion Analysis Toward Melanoma Detection: A Challenge at the 2017 International Symposium on Biomedical Imaging (ISBI), Hosted by the International Skin Imaging Collaboration (ISIC)](https://mlsanity.com/paper/1710.05006/) (2017)
- [U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation](https://mlsanity.com/paper/2401.04722/) (2024)
- [VM-UNet: Vision Mamba UNet for Medical Image Segmentation](https://mlsanity.com/paper/2402.02491/) (2024)
- [Global Filter Networks for Image Classification](https://mlsanity.com/paper/2107.00645/) (2021)
- [HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions](https://mlsanity.com/paper/2207.14284/) (2022)
- [MALUNet: A Multi-Attention and Light-weight UNet for Skin Lesion Segmentation](https://mlsanity.com/paper/2211.01784/) (2022)
- [LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation](https://mlsanity.com/paper/2403.05246/) (2024)
- [EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation](https://mlsanity.com/paper/2307.08473/) (2023)
- [VM-UNET-V2 Rethinking Vision Mamba UNet for Medical Image Segmentation](https://mlsanity.com/paper/2403.09157/) (2024)
- [H-vmunet: High-order Vision Mamba UNet for Medical Image Segmentation](https://mlsanity.com/paper/2403.13642/) (2024)
- [Devil is in Channels: Contrastive Single Domain Generalization for Medical Image Segmentation](https://mlsanity.com/paper/2306.05254/) (2023)
- [Attention Swin U-Net: Cross-Contextual Attention Mechanism for Skin Lesion Segmentation](https://mlsanity.com/paper/2210.16898/) (2022)
- [DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineation](https://mlsanity.com/paper/2308.02959/) (2023)

## Built on by (most cited first, 30 of 45)

- [State Space Model for New-Generation Network Alternative to Transformers: A Survey](https://mlsanity.com/paper/2404.09516/) (2024)
- [Vision Mamba: A Comprehensive Survey and Taxonomy](https://mlsanity.com/paper/2405.04404/) (2024)
- [A Survey on Visual Mamba](https://mlsanity.com/paper/2404.15956/) (2024)
- [DVMSR: Distillated Vision Mamba for Efficient Super-Resolution](https://mlsanity.com/paper/2405.03008/) (2024)
- [MemoryMamba: Memory-Augmented State Space Model for Defect Recognition](https://mlsanity.com/paper/2405.03673/) (2024)
- [Mamba in Vision: A Comprehensive Survey of Techniques and Applications](https://mlsanity.com/paper/2410.03105/) (2024)
- [A Comprehensive Survey of Mamba Architectures for Medical Image Analysis: Classification, Segmentation, Restoration and Beyond](https://mlsanity.com/paper/2410.02362/) (2024)
- [xLSTM-UNet can be an Effective 2D & 3D Medical Image Segmentation Backbone with Vision-LSTM (ViL) better than its Mamba Counterpart](https://mlsanity.com/paper/2407.01530/) (2024)
- [WeatherGen: A Unified Diverse Weather Generator for LiDAR Point Clouds via Spider Mamba Diffusion](https://mlsanity.com/paper/2504.13561/) (2025)
- [MK-UNet: Multi-kernel Lightweight CNN for Medical Image Segmentation](https://mlsanity.com/paper/2509.18493/) (2025)
- [SliceMamba with Neural Architecture Search for Medical Image Segmentation](https://mlsanity.com/paper/2407.08481/) (2024)
- [LFMamba: Light Field Image Super-Resolution with State Space Model](https://mlsanity.com/paper/2406.12463/) (2024)
- [MambaSCI: Efficient Mamba-UNet for Quad-Bayer Patterned Video Snapshot Compressive Imaging](https://mlsanity.com/paper/2410.14214/) (2024)
- [Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation](https://mlsanity.com/paper/2504.17515/) (2025)
- [AC-MAMBASEG: An adaptive convolution and Mamba-based architecture for enhanced skin lesion segmentation](https://mlsanity.com/paper/2405.03011/) (2024)
- [MUCM-Net: A Mamba Powered UCM-Net for Skin Lesion Segmentation](https://mlsanity.com/paper/2405.15925/) (2024)
- [SkinMamba: A Precision Skin Lesion Segmentation Architecture with Cross-Scale Global State Modeling and Frequency Boundary Guidance](https://mlsanity.com/paper/2409.10890/) (2024)
- [MambaLiteUNet: Cross-Gated Adaptive Feature Fusion for Robust Skin Lesion Segmentation](https://mlsanity.com/paper/2604.20286/) (2026)
- [A Reverse Mamba Attention Network for Pathological Liver Segmentation](https://mlsanity.com/paper/2502.18232/) (2025)
- [FuseUNet: A Multi-Scale Feature Fusion Method for U-like Networks](https://mlsanity.com/paper/2506.05821/) (2025)
- [UltraLBM-UNet: Ultralight Bidirectional Mamba-based Model for Skin Lesion Segmentation](https://mlsanity.com/paper/2512.21584/) (2025)
- [MHS-VM: Multi-Head Scanning in Parallel Subspaces for Vision Mamba](https://mlsanity.com/paper/2406.05992/) (2024)
- [EDMB: Edge Detector with Mamba](https://mlsanity.com/paper/2501.04846/) (2025)
- [UltraLight Med-Vision Mamba for Classification of Neoplastic Progression in Tubular Adenomas](https://mlsanity.com/paper/2508.09339/) (2025)
- [EEMS: Edge-Prompt Enhanced Medical Image Segmentation Based on Learnable Gating Mechanism](https://mlsanity.com/paper/2510.11287/) (2025)
- [BS-Mamba for Black-Soil Area Detection On the Qinghai-Tibetan Plateau](https://mlsanity.com/paper/2503.12495/) (2025)
- [ASP-VMUNet: Atrous Shifted Parallel Vision Mamba U-Net for Skin Lesion Segmentation](https://mlsanity.com/paper/2503.19427/) (2025)
- [Privacy-enhancing Sclera Segmentation Benchmarking Competition: SSBC 2025](https://mlsanity.com/paper/2508.10737/) (2025)
- [CD-Mamba: Cloud detection with long-range spatial dependency modeling](https://mlsanity.com/paper/2509.04729/) (2025)
- [CellMamba: Adaptive Mamba for Accurate and Efficient Cell Detection](https://mlsanity.com/paper/2512.21803/) (2025)

## Abstract (arXiv)

Traditionally for improving the segmentation performance of models, most approaches prefer to use adding more complex modules. And this is not suitable for the medical field, especially for mobile medical devices, where computationally loaded models are not suitable for real clinical environments due to computational resource constraints. Recently, state-space models (SSMs), represented by Mamba, have become a strong competitor to traditional CNNs and Transformers. In this paper, we deeply explore the key elements of parameter influence in Mamba and propose an UltraLight Vision Mamba UNet (UltraLight VM-UNet) based on this. Specifically, we propose a method for processing features in parallel Vision Mamba, named PVM Layer, which achieves excellent performance with the lowest computational load while keeping the overall number of processing channels constant. We conducted comparisons and ablation experiments with several state-of-the-art lightweight models on three skin lesion public datasets and demonstrated that the UltraLight VM-UNet exhibits the same strong performance competitiveness with parameters of only 0.049M and GFLOPs of 0.060. In addition, this study deeply explores the key elements of parameter influence in Mamba, which will lay a theoretical foundation for Mamba to possibly become a new mainstream module for lightweighting in the future. The code is available from https://github.com/wurenkai/UltraLight-VM-UNet .