Cardiac MRI: state of the art

PS Rajiah, CJ François, T Leiner - Radiology, 2023‏ - pubs.rsna.org
Cardiac MRI plays an important role in the evaluation of cardiovascular diseases (CVDs),
including ischemic heart disease, cardiomyopathy, valvular disease, congenital disease …

Deep learning in magnetic resonance image reconstruction

SS Chandra, M Bran Lorenzana, X Liu… - Journal of Medical …, 2021‏ - Wiley Online Library
Magnetic resonance (MR) imaging visualises soft tissue contrast in exquisite detail without
harmful ionising radiation. In this work, we provide a state‐of‐the‐art review on the use of …

Solving inverse problems with deep neural networks–robustness included?

M Genzel, J Macdonald, M März - IEEE transactions on pattern …, 2022‏ - ieeexplore.ieee.org
In the past five years, deep learning methods have become state-of-the-art in solving various
inverse problems. Before such approaches can find application in safety-critical fields, a …

Deep learning-based image reconstruction and motion estimation from undersampled radial k-space for real-time MRI-guided radiotherapy

ML Terpstra, M Maspero, F d'Agata… - Physics in Medicine …, 2020‏ - iopscience.iop.org
To enable magnetic resonance imaging (MRI)-guided radiotherapy with real-time
adaptation, motion must be quickly estimated with low latency. The motion estimate is used …

Dual-domain cascade of U-nets for multi-channel magnetic resonance image reconstruction

R Souza, M Bento, N Nogovitsyn, KJ Chung… - Magnetic resonance …, 2020‏ - Elsevier
The U-net is a deep-learning network model that has been used to solve a number of
inverse problems. In this work, the concatenation of two-element U-nets, termed the W-net …

A hybrid frequency-domain/image-domain deep network for magnetic resonance image reconstruction

R Souza, R Frayne - 2019 32nd SIBGRAPI conference on …, 2019‏ - ieeexplore.ieee.org
Decreasing magnetic resonance (MR) image acquisition times can potentially make MR
examinations more accessible. Compressed sensing (CS)-based image reconstruction …

MR‐zero meets RARE MRI: Joint optimization of refocusing flip angles and neural networks to minimize T2‐induced blurring in spin echo sequences

HN Dang, J Endres, S Weinmüller… - Magnetic …, 2023‏ - Wiley Online Library
Purpose An end‐to‐end differentiable 2D Bloch simulation is used to reduce T2 induced
blurring in single‐shot turbo spin echo sequences, also called rapid imaging with refocused …

Pyramid convolutional RNN for MRI image reconstruction

EZ Chen, P Wang, X Chen, T Chen… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
Fast and accurate MRI image reconstruction from undersampled data is crucial in clinical
practice. Deep learning based reconstruction methods have shown promising advances in …

Multi-coil MRI reconstruction challenge—assessing brain MRI reconstruction models and their generalizability to varying coil configurations

Y Beauferris, J Teuwen, D Karkalousos… - Frontiers in …, 2022‏ - frontiersin.org
Deep-learning-based brain magnetic resonance imaging (MRI) reconstruction methods
have the potential to accelerate the MRI acquisition process. Nevertheless, the scientific …

Primer and historical review on rapid cardiac CINE MRI

AD Curtis, HLM Cheng - Journal of Magnetic Resonance …, 2022‏ - Wiley Online Library
Acceleration is an important consideration when imaging moving organs such as the heart.
Not only does acceleration enable motion‐free scans but, more importantly, it lies at the …