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20202022
most citedBrain Tumor Segmentation Network Using Attention-based Fusion and Spatial Relationship Constraint

3 citations · 8 across the 6 of their papers we have counts for

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5 papers · 1 filter

eess.IV20221 cited

Cross-Modality Multi-Atlas Segmentation via Deep Registration and Label Fusion

Wangbin Ding, Lei Li, Xiahai Zhuang +1

Multi-atlas segmentation (MAS) is a promising framework for medical image segmentation. Generally, MAS methods register multiple atlases, i.e., medical images with corresponding la…

eess.IV20211 cited

Right Ventricular Segmentation from Short- and Long-Axis MRIs via Information Transition

Lei Li, Wangbin Ding, Liqun Huang +1

Right ventricular (RV) segmentation from magnetic resonance imaging (MRI) is a crucial step for cardiac morphology and function analysis. However, automatic RV segmentation from MR…

eess.IV2021

Unsupervised Multi-Modality Registration Network based on Spatially Encoded Gradient Information

Wangbin Ding, Lei Li, Xiahai Zhuang +1

Multi-modality medical images can provide relevant or complementary information for a target (organ, tumor or tissue). Registering multi-modality images to a common space can fuse…

eess.IV20203 cited

Brain Tumor Segmentation Network Using Attention-based Fusion and Spatial Relationship Constraint

Chenyu Liu, Wangbin Ding, Lei Li +4

Delineating the brain tumor from magnetic resonance (MR) images is critical for the treatment of gliomas. However, automatic delineation is challenging due to the complex appearanc…

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…