Present and future innovations in AI and cardiac MRI

MA Morales, WJ Manning, R Nezafat - Radiology, 2024 - pubs.rsna.org
Cardiac MRI is used to diagnose and treat patients with a multitude of cardiovascular
diseases. Despite the growth of clinical cardiac MRI, complicated image prescriptions and …

Artificial intelligence to reduce or eliminate the need for gadolinium-based contrast agents in brain and cardiac MRI: a literature review

CA Mallio, A Radbruch, K Deike-Hofmann… - Investigative …, 2023 - journals.lww.com
Brain and cardiac MRIs are fundamental noninvasive imaging tools, which can provide
important clinical information and can be performed without or with gadolinium-based …

[HTML][HTML] Radiomics and deep learning for myocardial scar screening in hypertrophic cardiomyopathy

AS Fahmy, EJ Rowin, A Arafati, T Al-Otaibi… - Journal of …, 2022 - Elsevier
Background Myocardial scar burden quantified using late gadolinium enhancement (LGE)
cardiovascular magnetic resonance (CMR), has important prognostic value in hypertrophic …

The road toward reproducibility of parametric mapping of the heart: a technical review

AC Ogier, A Bustin, H Cochet, J Schwitter… - Frontiers in …, 2022 - frontiersin.org
Parametric mapping of the heart has become an essential part of many cardiovascular
magnetic resonance imaging exams, and is used for tissue characterization and diagnosis …

Detection of liver cirrhosis in standard T2-weighted MRI using deep transfer learning

S Nowak, N Mesropyan, A Faron, W Block, M Reuter… - European …, 2021 - Springer
Objectives To investigate the diagnostic performance of deep transfer learning (DTL) to
detect liver cirrhosis from clinical MRI. Methods The dataset for this retrospective analysis …

[HTML][HTML] Accelerated cardiac T1 mapping in four heartbeats with inline MyoMapNet: a deep learning-based T1 estimation approach

R Guo, H El-Rewaidy, S Assana, X Cai, A Amyar… - Journal of …, 2022 - Elsevier
Purpose To develop and evaluate MyoMapNet, a rapid myocardial T 1 mapping approach
that uses fully connected neural networks (FCNN) to estimate T 1 values from four T 1 …

DeepFittingNet: A deep neural network‐based approach for simplifying cardiac T1 and T2 estimation with improved robustness

R Guo, D Si, Y Fan, X Qian, H Zhang… - Magnetic …, 2023 - Wiley Online Library
Purpose To develop and evaluate a deep neural network (DeepFittingNet) for T1/T2
estimation of the most commonly used cardiovascular MR mapping sequences to simplify …

Emerging techniques in cardiac magnetic resonance imaging

R Guo, S Weingärtner, P Šiurytė… - Journal of Magnetic …, 2022 - Wiley Online Library
Cardiovascular disease is the leading cause of death and a significant contributor of health
care costs. Noninvasive imaging plays an essential role in the management of patients with …

[HTML][HTML] Magnetic resonance myocardial T1ρ mapping: Technical overview, challenges, emerging developments, and clinical applications

A Bustin, WRT Witschey, RB van Heeswijk… - Journal of …, 2023 - Elsevier
The potential of cardiac magnetic resonance to improve cardiovascular care and patient
management is considerable. Myocardial T1-rho (T1ρ) mapping, in particular, has emerged …

[HTML][HTML] Myocardial T1-mapping and extracellular volume in pulmonary arterial hypertension: A systematic review and meta-analysis

S Alabed, L Saunders, P Garg, Y Shahin… - Magnetic resonance …, 2021 - Elsevier
Introduction Elevated myocardial T 1-mapping and extracellular volume (ECV) measured on
cardiac MR (CMR) imaging is associated with myocardial abnormalities such as oedema or …