Quantifying the impact of shape uncertainty on predicted arrhythmias

Corrado, C; Roney, CH; Razeghi, O; Lemus, JAS; Coveney, S; Sim, I; Williams, SE; O'Neill, MD; Wilkinson, RD; Clayton, RH; Niederer, SA

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Volume

153

Publisher

Elsevier

DOI

10.1016/j.compbiomed.2022.106528

Journal

COMPUTERS IN BIOLOGY AND MEDICINE

ISSN

0010-4825

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Abstract

Personalised computer models are increasingly used to diagnose cardiac arrhythmias and tailor treatment. Patient-specific models of the left atrium are often derived from pre-procedural imaging of anatomy and fibrosis. These images contain noise that can affect simulation predictions. There are few computationally tractable methods for propagating uncertainties from images to clinical predictions.

Authors

Corrado, C; Roney, CH; Razeghi, O; Lemus, JAS; Coveney, S; Sim, I; Williams, SE; O'Neill, MD; Wilkinson, RD; Clayton, RH

URI

https://qmro.qmul.ac.uk/xmlui/handle/123456789/94408

Collections

School of Engineering and Materials Science [3147]

Licence information

This item is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.