Computational methods for identifying left ventricle heart pathologies

Abstract

Globally, the cardiovascular diseases are the first cause of death. The early detection and quantification of these diseases can significantly reduce the mortality rate. Recent advances in cardiac MRI (CMRI) enable the detection of the left ventricle (LV) wall pathologies and the estimation of different quantification metrics that characterize the working of the heart. Examples of these metrics include the area of pathological tissue in the LV wall, the transmural extent of pathology, and other indexes such as wall thickening, functional strain, and the ejection fraction metrics. In the literature, several computational methods have been proposed in order to estimate these metrics based on using different CMRI acquisition techniques, such as cardiac-enhanced CMRI (CE-CMRI) and cine CMRI. This chapter overviews these computational methods and explains their basic ideas, focusing on the metrics extracted using CE-CMRI and cine CMRI.