activity
20202023
most citedMyoPS-Net: Myocardial Pathology Segmentation with Flexible Combination of Multi-Sequence CMR Images

54 citations · 74 across the 8 of their papers we have counts for

collaborators

8 papers

eess.IV2023★ 3 cited

Aligning Multi-Sequence CMR Towards Fully Automated Myocardial Pathology Segmentation

Wangbin Ding, Lei Li, Junyi Qiu +5

Myocardial pathology segmentation (MyoPS) is critical for the risk stratification and treatment planning of myocardial infarction (MI). Multi-sequence cardiac magnetic resonance (M…

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★ 54 cited

MyoPS-Net: Myocardial Pathology Segmentation with Flexible Combination of Multi-Sequence CMR Images

Junyi Qiu, Lei Li, Sihan Wang +4

Myocardial pathology segmentation (MyoPS) can be a prerequisite for the accurate diagnosis and treatment planning of myocardial infarction. However, achieving this segmentation is…

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.IV2020★ 2 cited

Anatomy Prior Based U-net for Pathology Segmentation with Attention

Yuncheng Zhou, Ke Zhang, Xinzhe Luo +2

Pathological area segmentation in cardiac magnetic resonance (MR) images plays a vital role in the clinical diagnosis of cardiovascular diseases. Because of the irregular shape and…

eess.IV2020★ 1 cited

Multi-Modality Pathology Segmentation Framework: Application to Cardiac Magnetic Resonance Images

Zhen Zhang, Chenyu Liu, Wangbin Ding +4

Multi-sequence of cardiac magnetic resonance (CMR) images can provide complementary information for myocardial pathology (scar and edema). However, it is still challenging to fuse…