Artificial Intelligence in Cardiovascular Magnetic Resonance Imaging

被引：0

作者：

Castellaccio, A. ^{[1
]}

Arostegui, N. Almeida ^{[1
]}

Jimenez, M. Palomo ^{[1
]}

Tapia, D. Quinones ^{[1
]}

Zurita, M. Bret ^{[1
]}

Galvan, E. Vano ^{[1
]}

机构：

[1] Hosp Univ Nuestra Senora del Rosario, Serv Resonancia Magnet & TC, Madrid, Spain

来源：

RADIOLOGIA | 2025年 / 67卷 / 02期

关键词：

Deep learning; Machine learning; Artificial intelligence; Cardiac magnetic resonance; Gadolinium; Fibrosis; LATE GADOLINIUM ENHANCEMENT; MYOCARDIAL-INFARCTION; DISEASE;

D O I：

10.1016/j.rx.2024.02.004

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

1002 ; 100207 ; 1009 ;

摘要：

Artificial intelligence is rapidly evolving and its possibilities are endless. Its primary applications in cardiac magnetic resonance imaging have focused on: image acquisition (in terms of acceleration and quality improvement); segmentation (in terms of saving time and reproducibility); tissue characterisation (including radiomic techniques and the non-contrast assessment of myocardial fibrosis); automatic diagnosis; and prognostic stratification. The aim of this article is to attempt to provide an overview of the current situation as preparation for the significant changes currently underway or imminent in the very near future. (c) 2024 SERAM. Published by Elsevier Espana, S.L.U. All rights reserved.

引用

页码：239 / 247

页数：9

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