Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/174752
Title: Cardiac magnetic resonance radiomics: basic principles and clinical perspectives
Author: Raisi Estabragh, Zahra
Izquierdo, Cristian
Campello Román, Víctor Manuel
Martin Isla, Carlos
Jaggi, Akshay
Harvey, Nicholas C.
Lekadir, Karim
Petersen, Steffen E.
Keywords: Ressonància magnètica
Diagnòstic per la imatge
Aprenentatge automàtic
Magnetic resonance
Diagnostic imaging
Machine learning
Issue Date: 6-Mar-2020
Publisher: Oxford University Press
Abstract: Radiomics is a novel image analysis technique, whereby voxel-level information is extracted from digital images and used to derive multiple numerical quantifiers of shape and tissue character. Cardiac magnetic resonance (CMR) is the reference imaging modality for assessment of cardiac structure and function. Conventional analysis of CMR scans is mostly reliant on qualitative image analysis and basic geometric quantifiers. Small proof-of-concept studies have demonstrated the feasibility and superior diagnostic accuracy of CMR radiomics analysis over conventional reporting. CMR radiomics has the potential to transform our approach to defining image phenotypes and, through this, improve diagnostic accuracy, treatment selection, and prognostication. The purpose of this article is to provide an overview of radiomics concepts for clinicians, with particular consideration of application to CMR. We will also review existing literature on CMR radiomics, discuss challenges, and consider directions for future work.
Note: Reproducció del document publicat a: https://doi.org/10.1093/ehjci/jeaa028
It is part of: European Heart Journal-Cardiovascular Imaging, 2020, vol. 21, num. 4, p. 349-356
URI: http://hdl.handle.net/2445/174752
Related resource: https://doi.org/10.1093/ehjci/jeaa028
ISSN: 2047-2404
Appears in Collections:Articles publicats en revistes (Matemàtiques i Informàtica)

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