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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 401–425 of 640 papers

TitleStatusHype
Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion DetectionCode0
Unsupervised Domain Adaptation with Semantic Consistency across Heterogeneous Modalities for MRI Prostate Lesion Segmentation—0
POPCORN: Progressive Pseudo-labeling with Consistency Regularization and Neighboring—0
PoissonSeg: Semi-Supervised Few-Shot Medical Image Segmentation via Poisson Learning—0
Adapting to Unseen Vendor Domains for MRI Lesion Segmentation—0
COVID-view: Diagnosis of COVID-19 using Chest CT—0
Self-Supervised Learning from Unlabeled Fundus Photographs Improves Segmentation of the Retina—0
Cohort Bias Adaptation in Aggregated Datasets for Lesion Segmentation—0
Dual-Attention Enhanced BDense-UNet for Liver Lesion Segmentation—0
Detecting when pre-trained nnU-Net models fail silently for Covid-19 lung lesion segmentation—0
Where is the disease? Semi-supervised pseudo-normality synthesis from an abnormal image—0
Volume of hyperintense inflammation (VHI): a deep learning-enabled quantitative imaging biomarker of inflammation load in spondyloarthritisCode0
Context-aware PolyUNet for Liver and Lesion Segmentation from Abdominal CT Images—0
Segmentation and ABCD rule extraction for skin tumors classification—0
Knowledge-aware Deep Framework for Collaborative Skin Lesion Segmentation and Melanoma Recognition—0
Decoupling Shape and Density for Liver Lesion Synthesis Using Conditional Generative Adversarial Networks—0
Dense Regression Activation Maps For Lesion Segmentation in CT scans of COVID-19 patients—0
Orthogonal Ensemble Networks for Biomedical Image SegmentationCode0
COVID-19 Lung Lesion Segmentation Using a Sparsely Supervised Mask R-CNN on Chest X-rays Automatically Computed from Volumetric CTsCode0
Stroke Lesion Segmentation with Visual Cortex Anatomy Alike Neural NetsCode0
Lesion Segmentation and RECIST Diameter Prediction via Click-driven Attention and Dual-path Connection—0
Weakly-Supervised Universal Lesion Segmentation with Regional Level Set Loss—0
Multiple Sclerosis Lesion Analysis in Brain Magnetic Resonance Images: Techniques and Clinical Applications—0
Auto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation—0
Uncertainty-Aware Temporal Self-Learning (UATS): Semi-Supervised Learning for Segmentation of Prostate Zones and Beyond—0
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