Investigating methods to enhance interpretability and performance in cardiac MRI for myocardial scarring diagnosis using convolutional neural network classification and One Match.

Investigating methods to enhance interpretability and performance in cardiac MRI for myocardial scarring diagnosis using convolutional neural network classification and One Match.

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Machine learning (ML) classification of myocardial scarring in cardiac MRI is often hindered by limited explainability, particularly with convolutional neural networks (CNNs). To address this, we developed One Match (OM), an algorithm that builds on template matching to improve on both the explainab...

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Bibliographic Details
Main Authors: Michael H Udin, Sara Armstrong, Alice Kai, Scott T Doyle, Saraswati Pokharel, Ciprian N Ionita, Umesh C Sharma
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0313971
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