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Skin Lesion Segmentation

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Showing 1–50 of 154 papers

TitleStatusHype
U-Net v2: Rethinking the Skip Connections of U-Net for Medical Image SegmentationCode6
UltraLight VM-UNet: Parallel Vision Mamba Significantly Reduces Parameters for Skin Lesion SegmentationCode3
A Multimodal Vision Foundation Model for Clinical DermatologyCode2
SkinMamba: A Precision Skin Lesion Segmentation Architecture with Cross-Scale Global State Modeling and Frequency Boundary GuidanceCode2
MobileUNETR: A Lightweight End-To-End Hybrid Vision Transformer For Efficient Medical Image SegmentationCode2
MCANet: Medical Image Segmentation with Multi-Scale Cross-Axis AttentionCode2
EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentationCode2
ASP-VMUNet: Atrous Shifted Parallel Vision Mamba U-Net for Skin Lesion SegmentationCode1
QTSeg: A Query Token-Based Architecture for Efficient 2D Medical Image SegmentationCode1
MambaU-Lite: A Lightweight Model based on Mamba and Integrated Channel-Spatial Attention for Skin Lesion SegmentationCode1
AC-MAMBASEG: An adaptive convolution and Mamba-based architecture for enhanced skin lesion segmentationCode1
DEU-Net: Dual-Encoder U-Net for Automated Skin Lesion SegmentationCode1
Only Positive Cases: 5-fold High-order Attention Interaction Model for Skin Segmentation Derived ClassificationCode1
SSG2: A new modelling paradigm for semantic segmentationCode1
Laplacian-Former: Overcoming the Limitations of Vision Transformers in Local Texture DetectionCode1
SamDSK: Combining Segment Anything Model with Domain-Specific Knowledge for Semi-Supervised Learning in Medical Image SegmentationCode1
Unlocking Fine-Grained Details with Wavelet-based High-Frequency Enhancement in TransformersCode1
DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion DelineationCode1
AViT: Adapting Vision Transformers for Small Skin Lesion Segmentation DatasetsCode1
FEDD -- Fair, Efficient, and Diverse Diffusion-based Lesion Segmentation and Malignancy ClassificationCode1
MDViT: Multi-domain Vision Transformer for Small Medical Image Segmentation DatasetsCode1
DAGrid: Directed Accumulator GridCode1
Enhancing Medical Image Segmentation with TransCeption: A Multi-Scale Feature Fusion ApproachCode1
DAE-Former: Dual Attention-guided Efficient Transformer for Medical Image SegmentationCode1
MALUNet: A Multi-Attention and Light-weight UNet for Skin Lesion SegmentationCode1
Attention Swin U-Net: Cross-Contextual Attention Mechanism for Skin Lesion SegmentationCode1
U-Net-based Models for Skin Lesion Segmentation: More Attention and AugmentationCode1
XBound-Former: Toward Cross-scale Boundary Modeling in TransformersCode1
Self-supervised Assisted Active Learning for Skin Lesion SegmentationCode1
FedMix: Mixed Supervised Federated Learning for Medical Image SegmentationCode1
MFSNet: A Multi Focus Segmentation Network for Skin Lesion SegmentationCode1
Cross-level Contrastive Learning and Consistency Constraint for Semi-supervised Medical Image SegmentationCode1
MT-TransUNet: Mediating Multi-Task Tokens in Transformers for Skin Lesion Segmentation and ClassificationCode1
Boundary-aware Transformers for Skin Lesion SegmentationCode1
MSRF-Net: A Multi-Scale Residual Fusion Network for Biomedical Image SegmentationCode1
Matthews Correlation Coefficient Loss for Deep Convolutional Networks: Application to Skin Lesion SegmentationCode1
CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image SegmentationCode1
DRU-net: An Efficient Deep Convolutional Neural Network for Medical Image SegmentationCode1
Illumination-based Transformations Improve Skin Lesion Segmentation in Dermoscopic ImagesCode1
Complementary Network with Adaptive Receptive Fields for Melanoma SegmentationCode1
Bi-Directional ConvLSTM U-Net with Densley Connected ConvolutionsCode1
Automatic skin lesion segmentation on dermoscopic images by the means of superpixel mergingCode1
Hierarchical Self-Prompting SAM: A Prompt-Free Medical Image Segmentation Framework—0
A Lightweight U-Net Model for Accurate Skin Lesion Segmentation—0
Multi-Granularity Vision Fastformer with Fusion Mechanism for Skin Lesion Segmentation—0
Self-Attention Diffusion Models for Zero-Shot Biomedical Image Segmentation: Unlocking New Frontiers in Medical Imaging—0
An Attentive Representative Sample Selection Strategy Combined with Balanced Batch Training for Skin Lesion Segmentation—0
ScaleFusionNet: Transformer-Guided Multi-Scale Feature Fusion for Skin Lesion SegmentationCode0
GS-TransUNet: Integrated 2D Gaussian Splatting and Transformer UNet for Accurate Skin Lesion AnalysisCode0
Image Segmentation: Inducing graph-based learningCode0
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