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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 301–325 of 640 papers

TitleStatusHype
Free-form Lesion Synthesis Using a Partial Convolution Generative Adversarial Network for Enhanced Deep Learning Liver Tumor Segmentation—0
ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation datasetCode1
Deep ensemble learning for segmenting tuberculosis-consistent manifestations in chest radiographs—0
SyntheX: Scaling Up Learning-based X-ray Image Analysis Through In Silico ExperimentsCode2
Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image SegmentationCode1
XBound-Former: Toward Cross-scale Boundary Modeling in TransformersCode1
A Survey on Deep Learning for Skin Lesion SegmentationCode0
Progressive Multi-scale Consistent Network for Multi-class Fundus Lesion SegmentationCode1
Salient Skin Lesion Segmentation via Dilated Scale-Wise Feature Fusion Network—0
Self-supervised Assisted Active Learning for Skin Lesion SegmentationCode1
SAN-Net: Learning Generalization to Unseen Sites for Stroke Lesion Segmentation with Self-Adaptive NormalizationCode0
FedMix: Mixed Supervised Federated Learning for Medical Image SegmentationCode1
MS Lesion Segmentation: Revisiting Weighting Mechanisms for Federated Learning—0
AAU-net: An Adaptive Attention U-net for Breast Lesions Segmentation in Ultrasound ImagesCode1
Class Balanced PixelNet for Neurological Image Segmentation—0
Segmentation Network with Compound Loss Function for Hydatidiform Mole Hydrops Lesion Recognition—0
Ischemic Stroke Lesion Segmentation Using Adversarial Learning—0
Segmentation-Consistent Probabilistic Lesion CountingCode0
CCAT-NET: A Novel Transformer Based Semi-supervised Framework for Covid-19 Lung Lesion Segmentation—0
MFSNet: A Multi Focus Segmentation Network for Skin Lesion SegmentationCode1
Auto-FedRL: Federated Hyperparameter Optimization for Multi-institutional Medical Image Segmentation—0
ModDrop++: A Dynamic Filter Network with Intra-subject Co-training for Multiple Sclerosis Lesion Segmentation with Missing ModalitiesCode1
Constrained unsupervised anomaly segmentationCode1
AGMR-Net: Attention Guided Multiscale Recovery framework for stroke segmentation—0
Factorizer: A Scalable Interpretable Approach to Context Modeling for Medical Image SegmentationCode1
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