Deep Learning-Based Algorithm for the Classification of Left Ventricle Segments by Hypertrophy Severity

In clinical practice, left ventricle hypertrophy (LVH) continues to pose a considerable challenge, highlighting the need for more reliable diagnostic approaches. This study aims to propose an automated framework for the quantification of LVH extent and the classification of myocardial segments accor...

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Bibliographic Details
Published in:	Journal of imaging Vol. 11; no. 7; p. 244
Main Authors:	Baccouch, Wafa, Hasnaoui, Bilel, Benameur, Narjes, Jemai, Abderrazak, Lahidheb, Dhaker, Labidi, Salam
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 20.07.2025 MDPI
Subjects:	Algorithms Artificial intelligence Artificial neural networks automatic quantification Automation Cardiomyopathy Cardiovascular disease cine-MRI Classification CNN classification Comparative analysis Deep learning Diagnosis Disease prevention Electrocardiography Heart enlargement Heart failure Heart ventricle, Left Hypertension Image segmentation left ventricle hypertrophy Machine learning Measurement Methods Metric space Neural networks Performance measurement Physiological aspects regional wall thickness Regression analysis Segmentation Segments Thickness Tunisia cine-MRI automatic quantification CNN classification regional wall thickness left ventricle hypertrophy
ISSN:	2313-433X, 2313-433X
Online Access:	Get full text
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