6 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…
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…
Style Transfer and Self-Supervised Learning Powered Myocardium Infarction Super-Resolution Segmentation
Lichao Wang, Jiahao Huang, Xiaodan Xing +7
This study proposes a pipeline that incorporates a novel style transfer model and a simultaneous super-resolution and segmentation model. The proposed pipeline aims to enhance diff…