Title: Myocardial infarction detection in late gadolinium enhancement cardiac MRI

Authors: Sarra Dali Youcef; Mahammed Messadi

Addresses: Laboratory of Biomedical Engineering, University of Tlemcen, Algeria ' Laboratory of Biomedical Engineering, University of Tlemcen, Algeria

Abstract: Cardiac magnetic resonance imaging (MRI) has become the most used technique for assessing myocardial viability. Myocardial segmentation is a fundamental step in the detection of myocardial infarction (MI) on late gadolinium enhancement (LGE) images. In this paper, we provide a system for automated myocardial infarct detection. The myocardial segmentation is applied to cine images and then transferred to LGE images, to subsequently detect myocardial infarction. We tested our approach on the Sunnybrook Cardiac Database. The proposed method shows remarkable accuracy. We obtained a dice similarity coefficient of 0.92 and an average perpendicular distance of 1.75 (mm) between automated and manual segmentation.

Keywords: left ventricle; cine MR images; late gadolinium enhanced MR images; myocardial infarct; viability.

DOI: 10.1504/IJMEI.2025.149547

International Journal of Medical Engineering and Informatics, 2025 Vol.17 No.6, pp.556 - 568

Received: 15 Oct 2022
Accepted: 05 Mar 2023
Published online: 07 Nov 2025 *

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