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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 351–400 of 640 papers

TitleStatusHype
Potential of Multimodal Large Language Models for Data Mining of Medical Images and Free-text Reports—0
PriorNet: lesion segmentation in PET-CT including prior tumor appearance information—0
Privacy-Preserving Federated Foundation Model for Generalist Ultrasound Artificial Intelligence—0
Progressive Adversarial Semantic Segmentation—0
Quality monitoring of federated Covid-19 lesion segmentation—0
Quasi-Conformal Convolution : A Learnable Convolution for Deep Learning on Riemann Surfaces—0
RECIST Weakly Supervised Lesion Segmentation via Label-Space Co-Training—0
ReFuSeg: Regularized Multi-Modal Fusion for Precise Brain Tumour Segmentation—0
RTNet: Relation Transformer Network for Diabetic Retinopathy Multi-lesion Segmentation—0
Saliency-based segmentation of dermoscopic images using color information—0
Salient Skin Lesion Segmentation via Dilated Scale-Wise Feature Fusion Network—0
SANet:Superpixel Attention Network for Skin Lesion Attributes Detection—0
Scale-aware Super-resolution Network with Dual Affinity Learning for Lesion Segmentation from Medical Images—0
Scanner Invariant Multiple Sclerosis Lesion Segmentation from MRI—0
SegHeD: Segmentation of Heterogeneous Data for Multiple Sclerosis Lesions with Anatomical Constraints—0
SegHeD+: Segmentation of Heterogeneous Data for Multiple Sclerosis Lesions with Anatomical Constraints and Lesion-aware Augmentation—0
Segmentation and ABCD rule extraction for skin tumors classification—0
Segmentation and Risk Score Prediction of Head and Neck Cancers in PET/CT Volumes with 3D U-Net and Cox Proportional Hazard Neural Networks—0
Segmentation Network with Compound Loss Function for Hydatidiform Mole Hydrops Lesion Recognition—0
Segmentation of Multiple Sclerosis lesion in brain MR images using Fuzzy C-Means—0
Segmenting Dermoscopic Images—0
Self-Attention Diffusion Models for Zero-Shot Biomedical Image Segmentation: Unlocking New Frontiers in Medical Imaging—0
Self-Learning AI Framework for Skin Lesion Image Segmentation and Classification—0
Self-supervised Brain Lesion Generation for Effective Data Augmentation of Medical Images—0
Self-Supervised Equivariant Regularization Reconciles Multiple Instance Learning: Joint Referable Diabetic Retinopathy Classification and Lesion Segmentation—0
Self-Supervised Learning from Unlabeled Fundus Photographs Improves Segmentation of the Retina—0
Semantic Segmentation of Skin Lesions using a Small Data Set—0
Semi-Automatic Algorithm for Breast MRI Lesion Segmentation Using Marker-Controlled Watershed Transformation—0
Semi-supervised few-shot learning for medical image segmentation—0
Semi-supervised Skin Lesion Segmentation via Transformation Consistent Self-ensembling Model—0
Sequential 3D U-Nets for Biologically-Informed Brain Tumor Segmentation—0
Severity Quantification and Lesion Localization of COVID-19 on CXR using Vision Transformer—0
Shallow vs deep learning architectures for white matter lesion segmentation in the early stages of multiple sclerosis—0
SHEAR-net: An End-to-End Deep Learning Approach for Single Push Ultrasound Shear Wave Elasticity Imaging—0
Simulation of acquisition shifts in T2 Flair MR images to stress test AI segmentation networks—0
Skin cancer reorganization and classification with deep neural network—0
Skincure: An Innovative Smart Phone-Based Application To Assist In Melanoma Early Detection And Prevention—0
SkiNet: A Deep Learning Solution for Skin Lesion Diagnosis with Uncertainty Estimation and Explainability—0
A survey, review, and future trends of skin lesion segmentation and classification—0
Skin Lesion Analysis toward Melanoma Detection: A Challenge at the International Symposium on Biomedical Imaging (ISBI) 2016, hosted by the International Skin Imaging Collaboration (ISIC)—0
Skin Lesion Analysis Towards Melanoma Detection Using Deep Learning Network—0
Towards Automated Melanoma Detection with Deep Learning: Data Purification and Augmentation—0
Skin Lesion Segmentation and Classification for ISIC 2018 Using Traditional Classifiers with Hand-Crafted Features—0
Skin Lesion Segmentation and Classification for ISIC 2018 by Combining Deep CNN and Handcrafted Features—0
Skin lesion segmentation and classification using deep learning and handcrafted features—0
Skin lesion segmentation based on preprocessing, thresholding and neural networks—0
Skin Lesion Segmentation: U-Nets versus Clustering—0
Skin Lesion Segmentation Using Atrous Convolution via DeepLab v3—0
Skin lesion segmentation using U-Net and good training strategies—0
SkinNet: A Deep Learning Framework for Skin Lesion Segmentation—0
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