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Lesion Segmentation

Lesion segmentation is the task of segmenting out lesions from other objects in medical based images.

( Image credit: D-UNet )

Papers

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Showing 11–20 of 640 papers

TitleStatusHype
MCANet: Medical Image Segmentation with Multi-Scale Cross-Axis AttentionCode2
EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentationCode2
SyntheX: Scaling Up Learning-based X-ray Image Analysis Through In Silico ExperimentsCode2
HWA-UNETR: Hierarchical Window Aggregate UNETR for 3D Multimodal Gastric Lesion SegmentationCode1
STPNet: Scale-aware Text Prompt Network for Medical Image SegmentationCode1
Learning from spatially inhomogenous data: resolution-adaptive convolutions for multiple sclerosis lesion segmentationCode1
ASP-VMUNet: Atrous Shifted Parallel Vision Mamba U-Net for Skin Lesion SegmentationCode1
A Data-Efficient Pan-Tumor Foundation Model for Oncology CT InterpretationCode1
CSC-PA: Cross-image Semantic Correlation via Prototype Attentions for Single-network Semi-supervised Breast Tumor SegmentationCode1
HCMA-UNet: A Hybrid CNN-Mamba UNet with Axial Self-Attention for Efficient Breast Cancer SegmentationCode1
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