ViM-UNet: Vision Mamba for Biomedical Segmentation

2024-04-11 · Anwai Archit, Constantin Pape

CNNs, most notably the UNet, are the default architecture for biomedical segmentation. Transformer-based approaches, such as UNETR, have been proposed to replace them, benefiting from a global field of view, but suffering from larger runtimes and higher parameter counts. The recent Vision Mamba architecture offers a compelling alternative to transformers, also providing a global field of view, but at higher efficiency. Here, we introduce ViM-UNet, a novel segmentation architecture based on it and compare it to UNet and UNETR for two challenging microscopy instance segmentation tasks. We find that it performs similarly or better than UNet, depending on the task, and outperforms UNETR while being more efficient. Our code is open source and documented at https://github.com/constantinpape/torch-em/blob/main/vimunet.md.

📄 PDF Abstract BibTeX arXiv:2404.07705

Code (1)

constantinpape/torch-em 공식 구현 pytorch

Tasks

Instance SegmentationMambaSegmentation Semantic Segmentation

Methods 이 논문이 사용한 방법론

Attention 설명 없음

Dense Connections Dense Connections, or Fully Connected Connections, are a type of layer in a deep neural network that use a linear operation where every input is connected to every output…

Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…

Position-Wise Feed-Forward Layer 설명 없음

Concatenated Skip Connection A Concatenated Skip Connection is a type of skip connection that seeks to reuse features by concatenating them to new layers, allowing more information to be retained from…

Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.

Batch Normalization 설명 없음

Max Pooling Max Pooling is a pooling operation that calculates the maximum value for patches of a feature map, and uses it to create a downsampled (pooled) feature map. It is usually…

xLSTM-UNet can be an Effective 2D & 3D Medical Image Segmentation Backbone with Vision-LSTM (ViL) better than its Mamba Counterpart

2024-07-01 · Tianrun Chen, Chaotao Ding, Lanyun Zhu, Tao Xu 외

Convolutional Neural Networks (CNNs) and Vision Transformers (ViT) have been pivotal in biomedical image segmentation, yet their ability to manage long-range dependencies remains constrained by inherent locality and comp…

3D Medical Imaging Segmentation image-classification Image Classification Image Segmentation+5

UU-Mamba: Uncertainty-aware U-Mamba for Cardiac Image Segmentation

2024-05-25 · Ting Yu Tsai, Li Lin, Shu Hu, Ming-Ching Chang 외

Biomedical image segmentation is critical for accurate identification and analysis of anatomical structures in medical imaging, particularly in cardiac MRI. Manual segmentation is labor-intensive, time-consuming, and pro…

Image Segmentation Mamba MRI segmentation Segmentation+1

UNetMamba: An Efficient UNet-Like Mamba for Semantic Segmentation of High-Resolution Remote Sensing Images

2024-08-21 · Enze Zhu, Zhan Chen, Dingkai Wang, Hanru Shi 외

Semantic segmentation of high-resolution remote sensing images is vital in downstream applications such as land-cover mapping, urban planning and disaster assessment.Existing Transformer-based methods suffer from the con…

Mamba Segmentation Semantic Segmentation The Semantic Segmentation Of Remote Sensing Imagery

Integrating Mamba Sequence Model and Hierarchical Upsampling Network for Accurate Semantic Segmentation of Multiple Sclerosis Legion

2024-03-26 · Kazi Shahriar Sanjid, Md. Tanzim Hossain, Md. Shakib Shahariar Junayed, Dr. Mohammad Monir Uddin

Integrating components from convolutional neural networks and state space models in medical image segmentation presents a compelling approach to enhance accuracy and efficiency. We introduce Mamba HUNet, a novel architec…

Decision Making Image Segmentation Lesion Segmentation Mamba+4

ASP-VMUNet: Atrous Shifted Parallel Vision Mamba U-Net for Skin Lesion Segmentation

2025-03-25 · Muyi Bao, Shuchang Lyu, Zhaoyang Xu, Qi Zhao 외

Skin lesion segmentation is a critical challenge in computer vision, and it is essential to separate pathological features from healthy skin for diagnostics accurately. Traditional Convolutional Neural Networks (CNNs) ar…

Image Segmentation Lesion Segmentation Mamba Medical Image Segmentation+3