1 citations · 3 across the 11 of their papers we have counts for
12 papers
RSFR: A Coarse-to-Fine Reconstruction Framework for Diffusion Tensor Cardiac MRI with Semantic-Aware Refinement
Jiahao Huang, Fanwen Wang, Pedro F. Ferreira +14
Cardiac diffusion tensor imaging (DTI) offers unique insights into cardiomyocyte arrangements, bridging the gap between microscopic and macroscopic cardiac function. However, its c…
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…
T1/T2 relaxation temporal modelling from accelerated acquisitions using a Latent Transformer
Fanwen Wang, Michael Tanzer, Mengyun Qiao +4
Quantitative cardiac magnetic resonance T1 and T2 mapping enable myocardial tissue characterisation but the lengthy scan times restrict their widespread clinical application. We pr…
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…
Efficient Post-processing of Diffusion Tensor Cardiac Magnetic Imaging Using Texture-conserving Deformable Registration
Fanwen Wang, Pedro F. Ferreira, Yinzhe Wu +8
Diffusion tensor cardiac magnetic resonance (DT-CMR) is a method capable of providing non-invasive measurements of myocardial microstructure. Image registration is essential to cor…
Deep Learning-based Diffusion Tensor Cardiac Magnetic Resonance Reconstruction: A Comparison Study
Jiahao Huang, Pedro F. Ferreira, Lichao Wang +11
In vivo cardiac diffusion tensor imaging (cDTI) is a promising Magnetic Resonance Imaging (MRI) technique for evaluating the micro-structure of myocardial tissue in the living hear…
Review of data types and model dimensionality for cardiac DTI SMS-related artefact removal
Michael Tanzer, Sea Hee Yook, Guang Yang +2
As diffusion tensor imaging (DTI) gains popularity in cardiac imaging due to its unique ability to non-invasively assess the cardiac microstructure, deep learning-based Artificial…
Faster Diffusion Cardiac MRI with Deep Learning-based breath hold reduction
Michael Tanzer, Pedro Ferreira, Andrew Scott +6
Diffusion Tensor Cardiac Magnetic Resonance (DT-CMR) enables us to probe the microstructural arrangement of cardiomyocytes within the myocardium in vivo and non-invasively, which n…