15 citations · 16 across the 4 of their papers we have counts for
9 papers
Is fitting error a reliable metric for assessing deformable motion correction in quantitative MRI?
Fanwen Wang, Ke Wen, Yaqing Luo +7
Quantitative MR (qMR) can provide numerical values representing the physical and chemical properties of the tissues. To collect a series of frames under varying settings, retrospec…
Lightweight Hypercomplex MRI Reconstruction: A Generalized Kronecker-Parameterized Approach
Haosen Zhang, Jiahao Huang, Yinzhe Wu +4
Magnetic Resonance Imaging (MRI) is crucial for clinical diagnostics but is hindered by prolonged scan times. Current deep learning models enhance MRI reconstruction but are often…
Groupwise Deformable Registration of Diffusion Tensor Cardiovascular Magnetic Resonance: Disentangling Diffusion Contrast, Respiratory and Cardiac Motions
Fanwen Wang, Yihao Luo, Ke Wen +9
Diffusion tensor based cardiovascular magnetic resonance (DT-CMR) offers a non-invasive method to visualize the myocardial microstructure. With the assumption that the heart is sta…
Low-rank based motion correction followed by automatic frame selection in DT-CMR
Fanwen Wang, Pedro F. Ferreira, Camila Munoz +8
Motivation: Post-processing of in-vivo diffusion tensor CMR (DT-CMR) is challenging due to the low SNR and variation in contrast between frames which makes image registration diffi…
Stain Consistency Learning: Handling Stain Variation for Automatic Digital Pathology Segmentation
Michael Yeung, Todd Watts, Sean YW Tan +4
Stain variation is a unique challenge associated with automated analysis of digital pathology. Numerous methods have been developed to improve the robustness of machine learning me…
High-Resolution Reference Image Assisted Volumetric Super-Resolution of Cardiac Diffusion Weighted Imaging
Yinzhe Wu, Jiahao Huang, Fanwen Wang +4
Diffusion Tensor Cardiac Magnetic Resonance (DT-CMR) is the only in vivo method to non-invasively examine the microstructure of the human heart. Current research in DT-CMR aims to…