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20182026
most citedMyoPS: A Benchmark of Myocardial Pathology Segmentation Combining Three-Sequence Cardiac Magnetic Resonance Images

10 citations · 25 across the 15 of their papers we have counts for

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eess.IV2023

Unsupervised Cardiac Segmentation Utilizing Synthesized Images from Anatomical Labels

Sihan Wang, Fuping Wu, Lei Li +3

Cardiac segmentation is in great demand for clinical practice. Due to the enormous labor of manual delineation, unsupervised segmentation is desired. The ill-posed optimization pro…

eess.IV2022

Decoupling Predictions in Distributed Learning for Multi-Center Left Atrial MRI Segmentation

Zheyao Gao, Lei Li, Fuping Wu +2

Distributed learning has shown great potential in medical image analysis. It allows to use multi-center training data with privacy protection. However, data distributions in local…

eess.IV2022★ 10 cited

MyoPS: A Benchmark of Myocardial Pathology Segmentation Combining Three-Sequence Cardiac Magnetic Resonance Images

Lei Li, Fuping Wu, Sihan Wang +29

Assessment of myocardial viability is essential in diagnosis and treatment management of patients suffering from myocardial infarction, and classification of pathology on myocardiu…

eess.IV2021★ 4 cited

Multi-Modality Cardiac Image Analysis with Deep Learning

Lei Li, Fuping Wu, Sihang Wang +1

Accurate cardiac computing, analysis and modeling from multi-modality images are important for the diagnosis and treatment of cardiac disease. Late gadolinium enhancement magnetic…

eess.IV2021

Unsupervised Domain Adaptation with Variational Approximation for Cardiac Segmentation

Fuping Wu, Xiahai Zhuang

Unsupervised domain adaptation is useful in medical image segmentation. Particularly, when ground truths of the target images are not available, domain adaptation can train a targe…