[HTML][HTML] Machine learning in cardiovascular magnetic resonance: basic concepts and applications

T Leiner, D Rueckert, A Suinesiaputra… - Journal of …, 2019 - Elsevier
Abstract Machine learning (ML) is making a dramatic impact on cardiovascular magnetic
resonance (CMR) in many ways. This review seeks to highlight the major areas in CMR …

The applications of artificial intelligence in cardiovascular magnetic resonance—a comprehensive review

A Argentiero, G Muscogiuri, MG Rabbat… - Journal of Clinical …, 2022 - mdpi.com
Cardiovascular disease remains an integral field on which new research in both the
biomedical and technological fields is based, as it remains the leading cause of mortality …

Cardiac Magnetic Resonance as Risk Stratification Tool in Non-Ischemic Dilated Cardiomyopathy Referred for Implantable Cardioverter Defibrillator Therapy—State …

A Argentiero, MC Carella, D Mandunzio… - Journal of Clinical …, 2023 - mdpi.com
Non-ischemic dilated cardiomyopathy (DCM) is a disease characterized by left ventricular
dilation and systolic dysfunction. Patients with DCM are at higher risk for ventricular …

Standardized image post-processing of cardiovascular magnetic resonance T1-mapping reduces variability and improves accuracy and consistency in myocardial …

V Carapella, H Puchta, E Lukaschuk, C Marini… - International journal of …, 2020 - Elsevier
Background Myocardial T1-mapping is increasingly used in multicentre studies and trials.
Inconsistent image analysis introduces variability, hinders differentiation of diseases, and …

[引用][C] Artificial Intelligence: Learning About the Future of Cardiovascular MR