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20202022
most citedMyoPS-Net: Myocardial Pathology Segmentation with Flexible Combination of Multi-Sequence CMR Images

54 citations · 71 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV202254 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.IV202210 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.IV20214 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.IV20202 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.IV20201 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…