Quantitative analysis of myocardial perfusion images

Myocardial perfusion imaging is a widely used test for the detection of coronary artery disease. Automated measurements of perfusion can be obtained from three-dimensional stress and rest images. The software segments the left ventricle of the heart and compares image intensities to normal subject database. In our research, we aim at reduction and ultimately elimination of human supervision in this process to improve overall reproducibility and accuracy for disease detection. We have developed several methods to this end such as automatic detection of potentially incorrect contours and direct measurement of stress-rest changes. Current state-of-the-art analysis methods demonstrate better reproducibility and similar accuracy when compared with experienced physicians. We aim to further improve the diagnostic accuracy by data mining techniques, combining several extracted image features with clinical information about the patients. Preliminary results show further improvements in accuracy, beyond that achieved by expert observers.