Myocardial infarction (MI) or acute myocardial infarction commonly known as heart attack is one of the major causes of cardiac death worldwide. It occurs when the blood supply to the portion of the heart muscle is blocked or stopped causing death of heart muscle cells. Early detection of MI will help to prevent the infarct expansion leading to left ventricle (LV) remodeling and further damage to the cardiac muscles. Timely identification of MI and the extent of LV remodeling are crucial to reduce the time taken for further tests, and save the cost due to early treatment. Echocardiography images are widely used to assess the differential diagnosis of normal and infarcted myocardium. The reading of ultrasound images is subjective due to interobserver variability and may lead to inconclusive findings which may increase the anxiety for patients. Hence, a computer-aided diagnostic (CAD) technique which uses echocardiography images of the heart coupled with pattern recognition algorithms can accurately classify normal and infarcted myocardium images. In this review paper, we have discussed the various components that are used to develop a reliable CAD system.