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HEJC, J. POSPISIL, D. NOVOTNA, P. PESL, M. JANOUSEK, O. RONZHINA, M. STAREK, Z.
Originální název
Segmentation of Atrial Electrical Activity in Intracardiac Electrograms (IECGs) Using Convolutional Neural Network (CNN) Trained on Small Imbalanced Dataset
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Timing pattern of intracardiac atrial activity recorded by multipolar catheter in the coronary sinus (CS) provides insightful information about the type and approximate origin of common non-complex arrhythmias. Depending on the anatomy of the CS, the atrial activity can be substantially disturbed by ventricular far field complex preventing accurate segmentation by convential methods. In this paper, we present small clinically validated database of 326 surface 12-lead and intracardiac electrograms (ECG and IEGs) and a simple deep learning framework for semantic beat-to-beat segmentation of atrial activity in CS recordings. The model is based on a residual convolutional neural network (CNN) combined with pyramidal upsampling decoder. It is capable to recognize well between atrial and ventricular signals recorded by decapolar CS catheter in multiple arrhythmic scenarios reaching dice score of 0.875 on evaluation dataset. To address a dataset size and imbalance issues, we have adopted several preprocessing and learning techniques with adequate evaluation of its impact on the model performance.
Klíčová slova
Cardiology; Complex networks; Convolution; Convolutional neural networks; Deep learning; Petroleum reservoir evaluation; Semantics
Autoři
HEJC, J.; POSPISIL, D.; NOVOTNA, P.; PESL, M.; JANOUSEK, O.; RONZHINA, M.; STAREK, Z.
Vydáno
1. 10. 2021
Nakladatel
IEEE
Místo
NEW YORK
ISBN
9781665479165
Kniha
Computing in Cardiology
Edice
September 2021
ISSN
2325-8861
Periodikum
Compuing in Cardiology 2013
Ročník
September
Číslo
1
Stát
Španělské království
Strany od
Strany do
4
Strany počet
URL
https://www.cinc.org/archives/2021/pdf/CinC2021-233.pdf
BibTex
@inproceedings{BUT182416, author="HEJC, J. and POSPISIL, D. and NOVOTNA, P. and PESL, M. and JANOUSEK, O. and RONZHINA, M. and STAREK, Z.", title="Segmentation of Atrial Electrical Activity in Intracardiac Electrograms (IECGs) Using Convolutional Neural Network (CNN) Trained on Small Imbalanced Dataset", booktitle="Computing in Cardiology", year="2021", series="September 2021", journal="Compuing in Cardiology 2013", volume="September", number="1", pages="1--4", publisher="IEEE", address="NEW YORK", doi="10.22489/CinC.2021.233", isbn="9781665479165", issn="2325-8861", url="https://www.cinc.org/archives/2021/pdf/CinC2021-233.pdf" }