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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 51–75 of 640 papers

TitleStatusHype
Exploring Vanilla U-Net for Lesion Segmentation from Whole-body FDG-PET/CT ScansCode1
Factorizer: A Scalable Interpretable Approach to Context Modeling for Medical Image SegmentationCode1
FedMix: Mixed Supervised Federated Learning for Medical Image SegmentationCode1
From FDG to PSMA: A Hitchhiker's Guide to Multitracer, Multicenter Lesion Segmentation in PET/CT ImagingCode1
Complementary Network with Adaptive Receptive Fields for Melanoma SegmentationCode1
HRDecoder: High-Resolution Decoder Network for Fundus Image Lesion SegmentationCode1
HWA-UNETR: Hierarchical Window Aggregate UNETR for 3D Multimodal Gastric Lesion SegmentationCode1
Illumination-based Transformations Improve Skin Lesion Segmentation in Dermoscopic ImagesCode1
Inconsistency Masks: Removing the Uncertainty from Input-Pseudo-Label PairsCode1
Applications of Deep Learning in Fundus Images: A ReviewCode1
Cross-level Contrastive Learning and Consistency Constraint for Semi-supervised Medical Image SegmentationCode1
LambdaUNet: 2.5D Stroke Lesion Segmentation of Diffusion-weighted MR ImagesCode1
Boundary-aware Transformers for Skin Lesion SegmentationCode1
ASP-VMUNet: Atrous Shifted Parallel Vision Mamba U-Net for Skin Lesion SegmentationCode1
Bi-Directional ConvLSTM U-Net with Densley Connected ConvolutionsCode1
Boosting multiple sclerosis lesion segmentation through attention mechanismCode1
Boundary loss for highly unbalanced segmentationCode1
Automatic skin lesion segmentation on dermoscopic images by the means of superpixel mergingCode1
Attention Swin U-Net: Cross-Contextual Attention Mechanism for Skin Lesion SegmentationCode1
Boosting multiple sclerosis lesion segmentation through attention mechanismCode1
AC-MAMBASEG: An adaptive convolution and Mamba-based architecture for enhanced skin lesion segmentationCode1
CarveMix: A Simple Data Augmentation Method for Brain Lesion SegmentationCode1
A Teacher-Student Framework for Semi-supervised Medical Image Segmentation From Mixed SupervisionCode1
CoactSeg: Learning from Heterogeneous Data for New Multiple Sclerosis Lesion SegmentationCode1
A high-order focus interaction model and oral ulcer dataset for oral ulcer segmentationCode1
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