An enhanced accessory pathway localization method for efficient treatment of Wolff-Parkinson-White syndrome

Sándor M. Szilágyi, László Szilágyi, Levente K. Görög, Constantin T. Luca, Dragoş Cozma, Gabriel Ivanica, Zoltán Benyó

Research output: Conference contribution

Abstract

This paper presents an analysis of the Arruda accessory pathway localization method for patients suffering from Wolff-Parkinson-White syndrome, with modifications to increase the overall performance. The Arruda method was tested on a total of 79 cases, and 91.1 % localization performance was reached. After a deeper analysis of each decision point of the Arruda localization method, we considered that the lead aVF is not as relevant as other used leads (I, II, III, V1). The branch of the decision tree, which evaluates the left ventricle positions, was entirely replaced using different decision criteria based of the same biological parameters. The modified algorithm significantly improves the localization performance in the left ventricle. The overall performance reaches 94.9 %. A high localization performance of non-invasive methods is relevant because it can enlighten the necessary invasive interventions, and also reduces the discomfort caused to the patient.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis and Applications - 13th Iberoamerican Congress on Pattern Recognition, CIARP 2008, Proceedings
PublisherSpringer Verlag
Pages269-276
Number of pages8
ISBN (Print)3540859195, 9783540859192
DOIs
Publication statusPublished - jan. 1 2008
Event13th Iberoamerican Congress on Pattern Recognition, CIARP 2008 - Havana, Cuba
Duration: szept. 9 2008szept. 12 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5197 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th Iberoamerican Congress on Pattern Recognition, CIARP 2008
CountryCuba
CityHavana
Period9/9/089/12/08

    Fingerprint

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Szilágyi, S. M., Szilágyi, L., Görög, L. K., Luca, C. T., Cozma, D., Ivanica, G., & Benyó, Z. (2008). An enhanced accessory pathway localization method for efficient treatment of Wolff-Parkinson-White syndrome. In Progress in Pattern Recognition, Image Analysis and Applications - 13th Iberoamerican Congress on Pattern Recognition, CIARP 2008, Proceedings (pp. 269-276). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5197 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-540-85920-8_33