Synthetic fibrosis distributions for data augmentation in predicting atrial fibrillation ablation outcomes: an in silico study

Synthetic fibrosis distributions for data augmentation in predicting atrial fibrillation ablation outcomes: an in silico study

IntroductionCardiac fibrosis influences atrial fibrillation (AF) progression and ablation outcomes, with late gadolinium enhancement (LGE) MRI providing a non-invasive tool to measure fibrosis distributions. While deep learning (DL) has shown promise in predicting ablation success, training such pip...

Full description

Saved in:
Bibliographic Details
Main Authors: Alexander M. Zolotarev, Kiane Johnson, Yusuf Mohammad, Omnia Alwazzan, Gregory Slabaugh, Caroline H. Roney
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-04-01
Series:Frontiers in Cardiovascular Medicine
Subjects:
atrial fibrillation
ablation
diffusion models
multi-modal fusion
computer vision
biophysical simulations
Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2025.1512356/full
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.frontiersin.org/articles/10.3389/fcvm.2025.1512356/full

Similar Items