Quality control-driven deep ensemble for accountable automated segmentation of cardiac magnetic resonance LGE and VNE images

Quality control-driven deep ensemble for accountable automated segmentation of cardiac magnetic resonance LGE and VNE images

BackgroundLate gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging is the gold standard for non-invasive myocardial tissue characterisation. However, accurate segmentation of the left ventricular (LV) myocardium remains a challenge due to limited training data and lack of qu...

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Bibliographic Details
Main Authors: Ricardo A. Gonzales, Daniel H. Ibáñez, Evan Hann, Iulia A. Popescu, Matthew K. Burrage, Yung P. Lee, İbrahim Altun, William S. Weintraub, Raymond Y. Kwong, Christopher M. Kramer, Stefan Neubauer, Hypertrophic Cardiomyopathy Registry (HCMR) Investigators, Oxford Acute Myocardial Infarction (OxAMI) Study, Vanessa M. Ferreira, Qiang Zhang, Stefan K. Piechnik
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-09-01
Series:Frontiers in Cardiovascular Medicine
Subjects:
data augmentation
generative adversarial networks
quality control
segmentation
late gadolinium enhancement
virtual native enhancement
Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2023.1213290/full

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