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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 1–50 of 640 papers

TitleStatusHype
U-Net v2: Rethinking the Skip Connections of U-Net for Medical Image SegmentationCode6
U-Net: Convolutional Networks for Biomedical Image SegmentationCode3
UltraLight VM-UNet: Parallel Vision Mamba Significantly Reduces Parameters for Skin Lesion SegmentationCode3
MobileUNETR: A Lightweight End-To-End Hybrid Vision Transformer For Efficient Medical Image SegmentationCode2
Vivim: a Video Vision Mamba for Medical Video SegmentationCode2
EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentationCode2
Longitudinal Segmentation of MS Lesions via Temporal Difference WeightingCode2
SyntheX: Scaling Up Learning-based X-ray Image Analysis Through In Silico ExperimentsCode2
MCANet: Medical Image Segmentation with Multi-Scale Cross-Axis AttentionCode2
A Multimodal Vision Foundation Model for Clinical DermatologyCode2
LesionLocator: Zero-Shot Universal Tumor Segmentation and Tracking in 3D Whole-Body ImagingCode2
SkinMamba: A Precision Skin Lesion Segmentation Architecture with Cross-Scale Global State Modeling and Frequency Boundary GuidanceCode2
H-vmunet: High-order Vision Mamba UNet for Medical Image SegmentationCode2
DRU-net: An Efficient Deep Convolutional Neural Network for Medical Image SegmentationCode1
DoubleU-Net: A Deep Convolutional Neural Network for Medical Image SegmentationCode1
Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT ImagesCode1
Diffusion Models for Implicit Image Segmentation EnsemblesCode1
DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion DelineationCode1
Domain and Content Adaptive Convolution based Multi-Source Domain Generalization for Medical Image SegmentationCode1
DuAT: Dual-Aggregation Transformer Network for Medical Image SegmentationCode1
Cross-level Contrastive Learning and Consistency Constraint for Semi-supervised Medical Image SegmentationCode1
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
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image SegmentationCode1
DeepLesion: Automated Deep Mining, Categorization and Detection of Significant Radiology Image Findings using Large-Scale Clinical Lesion AnnotationsCode1
DEU-Net: Dual-Encoder U-Net for Automated Skin Lesion SegmentationCode1
Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain ImagesCode1
A Foundation Model for Brain Lesion Segmentation with Mixture of Modality ExpertsCode1
ASC-Net : Adversarial-based Selective Network for Unsupervised Anomaly SegmentationCode1
DR-Unet104 for Multimodal MRI brain tumor segmentationCode1
CSC-PA: Cross-image Semantic Correlation via Prototype Attentions for Single-network Semi-supervised Breast Tumor SegmentationCode1
Complementary Network with Adaptive Receptive Fields for Melanoma SegmentationCode1
ChatCAD: Interactive Computer-Aided Diagnosis on Medical Image using Large Language ModelsCode1
Comprehensive Comparison of Deep Learning Models for Lung and COVID-19 Lesion Segmentation in CT scansCode1
D2A U-Net: Automatic Segmentation of COVID-19 Lesions from CT Slices with Dilated Convolution and Dual Attention MechanismCode1
Boosting multiple sclerosis lesion segmentation through attention mechanismCode1
Boosting multiple sclerosis lesion segmentation through attention mechanismCode1
Boundary-aware Transformers for Skin Lesion SegmentationCode1
AViT: Adapting Vision Transformers for Small Skin Lesion Segmentation DatasetsCode1
AADG: Automatic Augmentation for Domain Generalization on Retinal Image SegmentationCode1
CarveMix: A Simple Data Augmentation Method for Brain Lesion SegmentationCode1
CoactSeg: Learning from Heterogeneous Data for New Multiple Sclerosis Lesion SegmentationCode1
Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patientsCode1
AAU-net: An Adaptive Attention U-net for Breast Lesions Segmentation in Ultrasound ImagesCode1
Applications of Deep Learning in Fundus Images: A ReviewCode1
A Data-Efficient Pan-Tumor Foundation Model for Oncology CT InterpretationCode1
Constrained unsupervised anomaly segmentationCode1
A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES ChallengeCode1
DAGrid: Directed Accumulator GridCode1
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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