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Echocardiogram (echo) is the earliest and the primary tool for identifyingregional wall motion abnormalities (RWMA) in order to diagnose myocardialinfarction (MI) or commonly known as heart attack. This paper proposes a novelapproach, Active Polynomials, which can accurately and robustly estimate theglobal motion of the Left Ventricular (LV) wall from any echo in a robust andaccurate way. The proposed algorithm quantifies the true wall motion occurringin LV wall segments so as to assist cardiologists diagnose early signs of anacute MI. It further enables medical experts to gain an enhanced visualizationcapability of echo images through color-coded segments along with their"maximum motion displacement" plots helping them to better assess wall motionand LV Ejection-Fraction (LVEF). The outputs of the method can further helpecho-technicians to assess and improve the quality of the echocardiogramrecording. A major contribution of this study is the first public echo databasecollection composed by physicians at the Hamad Medical Corporation Hospital inQatar. The so-called HMC-QU database will serve as the benchmark for theforthcoming relevant studies. The results over the HMC-QU dataset show that theproposed approach can achieve high accuracy, sensitivity and precision in MIdetection even though the echo quality is quite poor, and the temporalresolution is low.

Left Ventricular Wall Motion Estimation by Active Polynomials for Acute Myocardial Infarction Detection