1 citations · 1 across the 4 of their papers we have counts for
4 papers
Imaging Transformer for MRI Denoising: a Scalable Model Architecture that enables SNR << 1 Imaging
Hui Xue, Sarah M. Hooper, Rhodri H. Davies +9
Purpose: To propose a flexible and scalable imaging transformer (IT) architecture with three attention modules for multi-dimensional imaging data and apply it to MRI denoising with…
SNRAware: Improved Deep Learning MRI Denoising with SNR Unit Training and G-factor Map Augmentation
Hui Xue, Sarah M. Hooper, Iain Pierce +9
To develop and evaluate a new deep learning MR denoising method that leverages quantitative noise distribution information from the reconstruction process to improve denoising perf…
Inline AI: Open-source Deep Learning Inference for Cardiac MR
Hui Xue, Rhodri H Davies, James Howard +8
Cardiac Magnetic Resonance (CMR) is established as a non-invasive imaging technique for evaluation of heart function, anatomy, and myocardial tissue characterization. Quantitative…
Imaging transformer for MRI denoising with the SNR unit training: enabling generalization across field-strengths, imaging contrasts, and anatomy
Hui Xue, Sarah Hooper, Azaan Rehman +11
The ability to recover MRI signal from noise is key to achieve fast acquisition, accurate quantification, and high image quality. Past work has shown convolutional neural networks…