Comparison between unipolar and bipolar electrograms for detecting rotor tip from 2D fibrillation model using image fusion. A simulation study. Duarte-Salazar, C., A., Orozco-Duque, A., Tobon, C., Peluffo-Ordonez, D., H., Guzman Luna, J., A., & Becerra, M., A. In 2016 IEEE Latin American Conference on Computational Intelligence (LA-CCI), pages 1-6, 11, 2016. IEEE. ![Comparison between unipolar and bipolar electrograms for detecting rotor tip from 2D fibrillation model using image fusion. A simulation study [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website doi abstract bibtex The atrial fibrillation (AF) is the most common arrhythmia, which generates the highest costs on clinical systems. Theory of the rotor is one of the most recent approaches to explain the mechanisms that maintain AF. The most promising treatment is the ablation, whose success depends on rotor tip location. In a previous research, the approximate entropy (ApEn) calculated on simulated electrograms from atrial models has shown high capability for detecting the rotor tip, however it needed a human final adjustment. In addition, this technique involves a high computational cost, which is a problem for its effective application. In this study, multiple features maps were generated and different combinations of them were conducted using wavelet image fusion. The rotor tip location when using image fusion, was similar to the results achieved with the methodology based on ApEn, however, our methodology did not require any manual adjustment, and the computational cost was reduced to 85%. This study includes a comparative analysis between unipolar and bipolar electrograms obtained from a simulated 2D model of a human atrial tissue under chronic AF.
@inproceedings{
title = {Comparison between unipolar and bipolar electrograms for detecting rotor tip from 2D fibrillation model using image fusion. A simulation study},
type = {inproceedings},
year = {2016},
keywords = {Atrial Fibrillation,Electrograms,Image Fusion,Rotor Tip},
pages = {1-6},
websites = {https://ieeexplore.ieee.org/document/7885712/},
month = {11},
publisher = {IEEE},
id = {9146ce52-1a1f-37a1-8c3c-4a53d2f7a547},
created = {2020-12-29T22:52:13.541Z},
file_attached = {false},
profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
last_modified = {2021-02-20T22:05:34.742Z},
read = {false},
starred = {false},
authored = {true},
confirmed = {true},
hidden = {false},
citation_key = {Duarte-Salazar2016},
private_publication = {false},
abstract = {The atrial fibrillation (AF) is the most common arrhythmia, which generates the highest costs on clinical systems. Theory of the rotor is one of the most recent approaches to explain the mechanisms that maintain AF. The most promising treatment is the ablation, whose success depends on rotor tip location. In a previous research, the approximate entropy (ApEn) calculated on simulated electrograms from atrial models has shown high capability for detecting the rotor tip, however it needed a human final adjustment. In addition, this technique involves a high computational cost, which is a problem for its effective application. In this study, multiple features maps were generated and different combinations of them were conducted using wavelet image fusion. The rotor tip location when using image fusion, was similar to the results achieved with the methodology based on ApEn, however, our methodology did not require any manual adjustment, and the computational cost was reduced to 85%. This study includes a comparative analysis between unipolar and bipolar electrograms obtained from a simulated 2D model of a human atrial tissue under chronic AF.},
bibtype = {inproceedings},
author = {Duarte-Salazar, Carlos A. and Orozco-Duque, Andres and Tobon, Catalina and Peluffo-Ordonez, Diego H. and Guzman Luna, Jaime A. and Becerra, Miguel A.},
doi = {10.1109/LA-CCI.2016.7885712},
booktitle = {2016 IEEE Latin American Conference on Computational Intelligence (LA-CCI)}
}
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