Reza Mosaffaripour

Reza Mosaffaripour

Reza Mosaffaripour
Automatic Estimation of Diagnostic Biomarkers for Myocardial Infarction of Left Ventricular Tissue
A.B. Lucas Secondary School

Coronary heart disease, which in severe cases leads to a heart attack, was titled the number one global killer in 2019 (W.H.O., 2020). A heart attack occurs when reduced blood supply causes the local damage and potential death of cardiac tissue (Rusu et al., 2018). Current methods for diagnosing heart attack damage have various disadvantages and do not fully capture the extent of damage (Mayo Clinic, 2020). This project investigates the use of an algorithm for heart attack diagnosis by estimating three parameters of the heart from CT images. The algorithm uses computational techniques previously unused in cardiac analysis, enabling it to automatically compute the three parameters and accurately determine the extent and location of heart attack damage. This method of diagnosis is ideal as it is non-invasive. This novel algorithm provides vital data to aid clinical diagnosis of heart attacks.

Award
Excellence Award – Senior Bronze Medal
Sponsor: Youth Science Canada