Detection of Cardiac Infarction in MRI C-SENC Images

Composite Strain Encoding (C-SENC) is an Magnetic Resonance Imaging (MRI) technique for acquiring simultaneous viability and functional and images of the heart. It combines two imaging techniques, Delayed Enhancement (DE) and Strain Encoding (SENC). In this work, a novel multi-stage method is proposed to identify ventricular infarction in the functional and viability images provided by C-SENC MRI. The proposed method is based on sequential application of Otsu's thresholding, morphological opening, square boundary tracing and the subtractive clustering algorithm. This method is tested on images of ten patients with and without myocardial infarction (MI). The resulting clustered images are compared with those marked up by expert cardiologists who assisted in validating results coming from the proposed method. Infarcted tissues are correctly identified using the proposed method with high levels of sensitivity and specificity. In this work, a novel, automatic, multi-stage method is proposed to identify different heart tissues from tuned images provided by Cardiac Magnetic Resonance (CMR) Composite Strain Encoding (C-SENC) images of transverse sections of the left ventricle (LV), and to identify infarcted myocardial tissues. This‎method‎is‎based‎on‎the‎application‎of‎Otsu's‎thresholding‎ technique, morphological opening, square boundary tracing and the subtractive clustering algorithm. Numerical simulations, real CMR images of patients and expert cardiologists'‎ markings‎ were‎ used‎ to‎ validate‎ the‎ proposed‎ method, which showed excellent results with respect to sensitivity and specificity.