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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 26–50 of 640 papers

TitleStatusHype
Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain ImagesCode1
A Foundation Model for Brain Lesion Segmentation with Mixture of Modality ExpertsCode1
Automatic Tumor Segmentation via False Positive Reduction Network for Whole-Body Multi-Modal PET/CT ImagesCode1
DR-Unet104 for Multimodal MRI brain tumor segmentationCode1
D2A U-Net: Automatic Segmentation of COVID-19 Lesions from CT Slices with Dilated Convolution and Dual Attention MechanismCode1
Comprehensive Comparison of Deep Learning Models for Lung and COVID-19 Lesion Segmentation in CT scansCode1
A Teacher-Student Framework for Semi-supervised Medical Image Segmentation From Mixed SupervisionCode1
Comprehensive framework for evaluation of deep neural networks in detection and quantification of lymphoma from PET/CT images: clinical insights, pitfalls, and observer agreement analysesCode1
DAE-Former: Dual Attention-guided Efficient Transformer for Medical Image SegmentationCode1
CarveMix: A Simple Data Augmentation Method for Brain Lesion SegmentationCode1
CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image SegmentationCode1
ChatCAD: Interactive Computer-Aided Diagnosis on Medical Image using Large Language ModelsCode1
Applications of Deep Learning in Fundus Images: A ReviewCode1
AADG: Automatic Augmentation for Domain Generalization on Retinal Image SegmentationCode1
ASC-Net : Adversarial-based Selective Network for Unsupervised Anomaly SegmentationCode1
Complementary Network with Adaptive Receptive Fields for Melanoma SegmentationCode1
ASP-VMUNet: Atrous Shifted Parallel Vision Mamba U-Net for Skin Lesion SegmentationCode1
AAU-net: An Adaptive Attention U-net for Breast Lesions Segmentation in Ultrasound ImagesCode1
Constrained unsupervised anomaly segmentationCode1
A Data-Efficient Pan-Tumor Foundation Model for Oncology CT InterpretationCode1
Attention Swin U-Net: Cross-Contextual Attention Mechanism for Skin Lesion SegmentationCode1
Automatic segmentation of spinal multiple sclerosis lesions: How to generalize across MRI contrasts?Code1
Automatic skin lesion segmentation on dermoscopic images by the means of superpixel mergingCode1
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localizationCode1
AC-MAMBASEG: An adaptive convolution and Mamba-based architecture for enhanced skin lesion segmentationCode1
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