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Quantifying and Visualizing Uncertainty for Source Localisation in Electrocardiographic Imaging

by Dennis Njeru, Tushar M Athawale, Jessie France, Chris Johnson
Publication Type
Journal Name
Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization
Publication Date
Page Numbers
812 to 822

Electrocardiographic imaging (ECGI) presents a clinical opportunity to noninvasively understand the sources of arrhythmias for individual patients. To help increase the effectiveness of ECGI, we provide new ways to visualise associated measurement and modelling errors. In this paper, we study source localisation uncertainty in two steps: First, we perform Monte Carlo simulations of a simple inverse ECGI source localisation model with error sampling to understand the variations in ECGI solutions. Second, we present multiple visualisation techniques, including confidence maps, level-sets, and topology-based visualisations, to better understand uncertainty in source localization. Our approach offers a new way to study uncertainty in the ECGI pipeline.