DOI: 10.36347/sjams.2017.v05i09.045

Pages: 3727-3732

Myocardial infarction is the irreversible death of the heart due to lack of oxygen that occur when the blood supply is reduced or cutoff and isn't restored in an appropriate period of time. This study aim to assessment of ejection Fraction (EF) End Systolic Volume (ESV) and End Diastolic Volume (EDV) in myocardial perfusion imaging (SPECT) at the heart in stress status test from the heart at rest status test using a function written in the Interactive Data Language (IDL) software to normalize the image to range of count that classify the muscles of the heart to four classes normal, mild, moderate and severe, and recognize each part of the images as one of the classes. Same process applied to subsequent slice for the whole heart, and the number of pixels in each part counted to found a percentage of the heart classes. The result shows that we can estimate the EF with accuracy (90%±5%), ESV with accuracy (95%±3%) and EDV with accuracy (83%±5%) of the heart at stress status test from rest status test without stressing the patient.