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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 251–300 of 640 papers

TitleStatusHype
Cross-Task Attention Network: Improving Multi-Task Learning for Medical Imaging Applications—0
Domain Adaptive Medical Image Segmentation via Adversarial Learning of Disease-Specific Spatial Patterns—0
Expert Knowledge-guided Geometric Representation Learning for Magnetic Resonance Imaging-based Glioma Grading—0
Explaining Uncertainty in Multiple Sclerosis Lesion Segmentation Beyond Prediction Errors—0
Adapting to Unseen Vendor Domains for MRI Lesion Segmentation—0
Interactive Segmentation and Report Generation for CT Images—0
Ischemic Stroke Lesion Segmentation in CT Perfusion Scans using Pyramid Pooling and Focal Loss—0
Cross-Domain Federated Learning in Medical Imaging—0
Automated ischemic stroke lesion segmentation from 3D MRI—0
CovTANet: A Hybrid Tri-level Attention Based Network for Lesion Segmentation, Diagnosis, and Severity Prediction of COVID-19 Chest CT Scans—0
CovSegNet: A Multi Encoder-Decoder Architecture for Improved Lesion Segmentation of COVID-19 Chest CT Scans—0
Automated external cervical resorption segmentation in cone-beam CT using local texture features—0
A Multi-task Framework for Skin Lesion Detection and Segmentation—0
COVID-view: Diagnosis of COVID-19 using Chest CT—0
GLAM: Glomeruli Segmentation for Human Pathological Lesions using Adapted Mouse Model—0
Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: emerging machine learning techniques and future avenues—0
Context-aware PolyUNet for Liver and Lesion Segmentation from Abdominal CT Images—0
A Multi-stage Framework with Context Information Fusion Structure for Skin Lesion Segmentation—0
Input Data Adaptive Learning (IDAL) for Sub-acute Ischemic Stroke Lesion Segmentation—0
Integrating Mamba Sequence Model and Hierarchical Upsampling Network for Accurate Semantic Segmentation of Multiple Sclerosis Legion—0
Conditional Generative Refinement Adversarial Networks for Unbalanced Medical Image Semantic Segmentation—0
Automated assessment of disease severity of COVID-19 using artificial intelligence with synthetic chest CT—0
Automated analysis of diabetic retinopathy using vessel segmentation maps as inductive bias—0
Grading and Anomaly Detection for Automated Retinal Image Analysis using Deep Learning—0
Auto-Lesion Segmentation with a Novel Intensity Dark Channel Prior for COVID-19 Detection—0
Comparative Analysis of Unsupervised Algorithms for Breast MRI Lesion Segmentation—0
Comparative Analysis of Automatic Skin Lesion Segmentation with Two Different Implementations—0
Auto-FedRL: Federated Hyperparameter Optimization for Multi-institutional Medical Image Segmentation—0
Acute ischemic stroke lesion segmentation in non-contrast CT images using 3D convolutional neural networks—0
Integrating Radiomics with Deep Learning Enhances Multiple Sclerosis Lesion Delineation—0
Ischemic Stroke Lesion Segmentation Using Adversarial Learning—0
Collaborative Learning of Semi-Supervised Segmentation and Classification for Medical Images—0
Cohort Bias Adaptation in Aggregated Datasets for Lesion Segmentation—0
Auto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation—0
Co-Heterogeneous and Adaptive Segmentation from Multi-Source and Multi-Phase CT Imaging Data: A Study on Pathological Liver and Lesion Segmentation—0
Coarse Retinal Lesion Annotations Refinement via Prototypical Learning—0
A Unified Multi-Phase CT Synthesis and Classification Framework for Kidney Cancer Diagnosis with Incomplete Data—0
Improving Lesion Segmentation in Medical Images by Global and Regional Feature Compensation—0
Clinical Inspired MRI Lesion Segmentation—0
4D Deep Learning for Multiple-Sclerosis Lesion Activity Segmentation—0
Class Balanced PixelNet for Neurological Image Segmentation—0
Improving Lesion Segmentation in FDG-18 Whole-Body PET/CT scans using Multilabel approach: AutoPET II challenge—0
Improving Multiple Sclerosis Lesion Segmentation Across Clinical Sites: A Federated Learning Approach with Noise-Resilient Training—0
Channel Attention Separable Convolution Network for Skin Lesion Segmentation—0
Attention-based CT Scan Interpolation for Lesion Segmentation of Colorectal Liver Metastases—0
Improved inter-scanner MS lesion segmentation by adversarial training on longitudinal data—0
Hierarchical Self-Prompting SAM: A Prompt-Free Medical Image Segmentation Framework—0
Hierarchical Fine-Tuning for joint Liver Lesion Segmentation and Lesion Classification in CT—0
CCAT-NET: A Novel Transformer Based Semi-supervised Framework for Covid-19 Lung Lesion Segmentation—0
HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation—0
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