Journal article
Interpretable machine learning for automated left ventricular scar quantification in hypertrophic cardiomyopathy patients
Abstract
Scar quantification on cardiovascular magnetic resonance (CMR) late gadolinium enhancement (LGE) images is important in risk stratifying patients with hypertrophic cardiomyopathy (HCM) due to the importance of scar burden in predicting clinical outcomes. We aimed to develop a machine learning (ML) model that contours left ventricular (LV) endo- and epicardial borders and quantifies CMR LGE images from HCM patients.We retrospectively studied …
Authors
Navidi Z; Sun J; Chan RH; Hanneman K; Al-Arnawoot A; Munim A; Rakowski H; Maron MS; Woo A; Wang B
Journal
PLOS Digital Health, Vol. 2, No. 1,
Publisher
Public Library of Science (PLoS)
DOI
10.1371/journal.pdig.0000159
ISSN
2767-3170