  Echocardiogram (echo) is the earliest and the primary tool for identifying
regional wall motion abnormalities (RWMA) in order to diagnose myocardial
infarction (MI) or commonly known as heart attack. This paper proposes a novel
approach, Active Polynomials, which can accurately and robustly estimate the
global motion of the Left Ventricular (LV) wall from any echo in a robust and
accurate way. The proposed algorithm quantifies the true wall motion occurring
in LV wall segments so as to assist cardiologists diagnose early signs of an
acute MI. It further enables medical experts to gain an enhanced visualization
capability of echo images through color-coded segments along with their
"maximum motion displacement" plots helping them to better assess wall motion
and LV Ejection-Fraction (LVEF). The outputs of the method can further help
echo-technicians to assess and improve the quality of the echocardiogram
recording. A major contribution of this study is the first public echo database
collection composed by physicians at the Hamad Medical Corporation Hospital in
Qatar. The so-called HMC-QU database will serve as the benchmark for the
forthcoming relevant studies. The results over the HMC-QU dataset show that the
proposed approach can achieve high accuracy, sensitivity and precision in MI
detection even though the echo quality is quite poor, and the temporal
resolution is low.
