54 citations · 114 across the 5 of their papers we have counts for
5 papers
Improved Accuracy and Precision In Simultaneous Myocardial T1 and T2 mapping with Multi-Parametric SASHA (mSASHA)
Kelvin Chow, Genevieve Hayes, Jacqueline A Flewitt +7
Purpose: To develop and validate a multi-parametric SAturation-recovery single-SHot Acquisition (mSASHA) cardiac T1 and T2 mapping technique with high accuracy and precision in a s…
Landmark detection in Cardiac Magnetic Resonance Imaging Using A Convolutional Neural Network
Hui Xue, Jessica Artico, Marianna Fontana +3
Purpose: To develop a convolutional neural network (CNN) solution for robust landmark detection in cardiac MR images. Methods: This retrospective study included cine, LGE and T1 ma…
Automated Inline Analysis of Myocardial Perfusion MRI with Deep Learning
Hui Xue, Rhodri Davies, Louis AE Brown +6
Recent development of quantitative myocardial blood flow (MBF) mapping allows direct evaluation of absolute myocardial perfusion, by computing pixel-wise flow maps. Clinical studie…
Automatic In-line Quantitative Myocardial Perfusion Mapping: processing algorithm and implementation
Hui Xue, Louise A. E. Brown, Sonia Nielles-Vallespin +2
Quantitative myocardial perfusion mapping has advantages over qualitative assessment, including the ability to detect global flow reduction. However, it is not clinically available…
Automated Detection of Left Ventricle in Arterial Input Function Images for Inline Perfusion Mapping using Deep Learning: A study of 15,000 Patients
Hui Xue, Ethan Tseng, Kristopher D Knott +6
Quantification of myocardial perfusion has the potential to improve detection of regional and global flow reduction. Significant effort has been made to automate the workflow, wher…