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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 226–250 of 640 papers

TitleStatusHype
Deconvolutional Feature Stacking for Weakly-Supervised Semantic Segmentation—0
Decomposing and Coupling Saliency Map for Lesion Segmentation in Ultrasound Images—0
Automatic detection of lesion load change in Multiple Sclerosis using convolutional neural networks with segmentation confidence—0
Automating Vitiligo Skin Lesion Segmentation Using Convolutional Neural Networks—0
An Ultra-Fast Method for Simulation of Realistic Ultrasound Images—0
Data-Driven Color Augmentation Techniques for Deep Skin Image Analysis—0
Dual-Attention Enhanced BDense-UNet for Liver Lesion Segmentation—0
Automatic acute ischemic stroke lesion segmentation using semi-supervised learning—0
Automated soft tissue lesion detection and segmentation in digital mammography using a u-net deep learning network—0
An Attentive Representative Sample Selection Strategy Combined with Balanced Batch Training for Skin Lesion Segmentation—0
A Point-Neighborhood Learning Framework for Nasal Endoscope Image Segmentation—0
DynSegNet:Dynamic Architecture Adjustment for Adversarial Learning in Segmenting Hemorrhagic Lesions from Fundus Images—0
EAGLE: An Efficient Global Attention Lesion Segmentation Model for Hepatic Echinococcosis—0
Efficient Folded Attention for 3D Medical Image Reconstruction and Segmentation—0
AutoPET Challenge: Tumour Synthesis for Data Augmentation—0
Frequency and Spatial domain based Saliency for Pigmented Skin Lesion Segmentation—0
Election of Collaborators via Reinforcement Learning for Federated Brain Tumor Segmentation—0
From Semantic Segmentation of Natural Images to Medical Image Segmentation Using ViT-Based Architectures—0
Lesion Segmentation in Ultrasound Using Semi-pixel-wise Cycle Generative Adversarial Nets—0
Automated Segmentation of Ischemic Stroke Lesions in Non-Contrast Computed Tomography Images for Enhanced Treatment and Prognosis—0
An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection—0
FMaMIL: Frequency-Driven Mamba Multi-Instance Learning for Weakly Supervised Lesion Segmentation in Medical Images—0
Ensemble of Multi-sized FCNs to Improve White Matter Lesion Segmentation—0
CT-To-MR Conditional Generative Adversarial Networks for Ischemic Stroke Lesion Segmentation—0
CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement—0
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