Detecting Anatomy Openings in the Left Atrium Via a Triangular Ultrasonic Array Using Deep Learning

Cardiac arrhythmia is the clinical term for the set of diseases wherein the heart beats irregularly. A widespread treatment is ablating the arrhythmia maintaining regions, which requires electro-anatomical mapping. A proposed sparse ultrasonic/electrode array can potentially map the anatomy and acti...

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Bibliographic Details
Main Authors: Baram, Alon, Ovadia, Oded, Zurakhov, Grigoriy, Giyras, Raja, Turkel, Eli, Greenspan, Hayit
Format: Conference Proceeding
Language:English
Subjects:
Arrhythmia
Biological system modeling
Deep learning
Heart
Heart beat
Real-time systems
Robustness
Online Access:Request full text
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Summary:Cardiac arrhythmia is the clinical term for the set of diseases wherein the heart beats irregularly. A widespread treatment is ablating the arrhythmia maintaining regions, which requires electro-anatomical mapping. A proposed sparse ultrasonic/electrode array can potentially map the anatomy and activity in real time. However, a limited amount of elements causes a difficulty in mapping anatomical openings. We propose a deep learning model to increase the mapping capacity. We empirically show that our proposed method is able to accurately detect openings in a heart chamber anatomy simulation. We further improve the accuracy of the model by adding Fourier-based pre-processing steps. Finally, we demonstrate the robustness of the model to changes in the physical parameters of the problem.
ISSN:1945-8452
DOI:10.1109/ISBI53787.2023.10230793