Computer Aided Analysis of Late Gadolinium Enhanced Cardiac MRI

Abstract

Viability assessment of the myocardium after myocardial infarction is essential for diagnosis and therapy planning. Among various clinical cardiac scans, late gadolinium enhanced (LGE) cardiac magnetic resonance (CMR) imaging can directly visualize and thus discriminate non-viable myocardium (i.e., infarcts) from normal myocardium via hyper-enhanced intensities. Since manual analysis of LGE CMR images is not only time-consuming but also subject to inter-observer variation, computer aided automatic techniques are of great research values. In this thesis, we present a complete 3D framework for automatic analysis of LGE CMR images. This framework achieves 3D segmentation of the myocardium as well as 3D classification of infarcts within the segmented myocardium, with robust and effective preprocessing measures overcoming misalignment artifact and intensity inconsistency across slices. Experimental results demonstrated that the framework can produce accurate and objective quantification of LGE CMR images and has the potential to be developed further as a clinical tool.