Comparative Analysis of Deep Learning Methods for Classification of Ablated Regions in Hyperspectral Images of Atrial Tissue

Radiofrequency ablation (RFA) is used to treat atrial fibrillation (AF). Viability gaps between ablated regions can lead to AF recurrence; thus, correctly detecting RFA lesions is important for successful treatment. Hyperspectral imaging (HSI) has been previously shown to aid in visualizing RFA-affe...

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Bibliographic Details
Main Authors:	Yeva Gabrielyan, Arpi Hunanyan, Sona Bezirganyan, Lusine Davtyan, Ani Avetisyan, Narine Sarvazyan, Aram Butavyan, Varduhi Yeghiazaryan
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Series:	IEEE Access
Subjects:	Atrial tissue ablation comparative analysis convolutional neural networks deep learning graph neural networks hyperspectral image classification
Online Access:	https://ieeexplore.ieee.org/document/10891579/
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Comparative Analysis of Deep Learning Methods for Classification of Ablated Regions in Hyperspectral Images of Atrial Tissue

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