Effect of Segmentation Variation on ECG Imaging

12Citations
Citations of this article
13Readers
Mendeley users who have this article in their library.

Abstract

ECG imaging (ECGI) is the process of calculating electrical cardiac activity from body surface recordings from the geometry and conductivity of the torso volume. A key first step to create geometric models for ECGI and a possible source of considerable variability is to segment the surface of the heart. We hypothesize that this variation in cardiac segmentation will produce variation in the computed ventricular surface potentials from ECGI. To evaluate this hypothesis, we leveraged the resources of the Consortium for ECG Imaging (CEI) to carry out a comparison of ECGI results from the same body surface potentials and multiple ventricular segmentations. We found that using the different segmentations produced variability in the computed ventricular surface potentials. Not surprisingly, locations of greater variance in the computed potential correlated to locations of greater variance in the segmentations, for example near the pulmonary artery and basal anterior left ventricular wall. Our results indicate that ECGI may be more sensitive to segmentation errors on the anterior epicardial surface than on other areas of the heart.

Cite

CITATION STYLE

APA

Tate, J. D., Zemzemi, N., Good, W. W., Van Dam, P., Brooks, D. H., & Macleod, R. S. (2018). Effect of Segmentation Variation on ECG Imaging. In Computing in Cardiology (Vol. 2018-September). IEEE Computer Society. https://doi.org/10.22489/CinC.2018.374

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free