An Automated Tool for the Detection of Electrocardiographic Diagnostic Features based on Spatial Aggregation and Computational Geometry

Liliana Ironi, Stefania Tentoni

2011

Abstract

In this work we focus on Electrocardiographic diagnosis based on epicardial activation fields. The identification, within an activation map, of specific patterns that are known to characterize classes of pathologies provides an important support to the diagnosis of rhythm disturbances that can be missed by routine low resolution ECGs. Through an approach grounded on the integration of a Spatial Aggregation (SA) method with concepts borrowed from Computational Geometry, we propose a computational framework to automatically extract, from input epicardial activation data, a few basic features that characterize the wavefront propagation, as well as amore specific set of diagnostic features that identify an important class of rhythm pathologies due to block of conduction.

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Paper Citation


in Harvard Style

Ironi L. and Tentoni S. (2011). An Automated Tool for the Detection of Electrocardiographic Diagnostic Features based on Spatial Aggregation and Computational Geometry . In Proceedings of the 2nd International Workshop on Medical Image Analysis and Description for Diagnosis Systems - Volume 1: MIAD, (BIOSTEC 2011) ISBN 978-989-8425-38-6, pages 3-12. DOI: 10.5220/0003197500030012


in Bibtex Style

@conference{miad11,
author={Liliana Ironi and Stefania Tentoni},
title={An Automated Tool for the Detection of Electrocardiographic Diagnostic Features based on Spatial Aggregation and Computational Geometry},
booktitle={Proceedings of the 2nd International Workshop on Medical Image Analysis and Description for Diagnosis Systems - Volume 1: MIAD, (BIOSTEC 2011)},
year={2011},
pages={3-12},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003197500030012},
isbn={978-989-8425-38-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Workshop on Medical Image Analysis and Description for Diagnosis Systems - Volume 1: MIAD, (BIOSTEC 2011)
TI - An Automated Tool for the Detection of Electrocardiographic Diagnostic Features based on Spatial Aggregation and Computational Geometry
SN - 978-989-8425-38-6
AU - Ironi L.
AU - Tentoni S.
PY - 2011
SP - 3
EP - 12
DO - 10.5220/0003197500030012