Abstract
Myocardial perfusion imaging (MPI) is a widely used and non-invasive diagnostic method for the detection of patients with suspected or known ischemic heart disease. MPI test is commonly realized by single photon emission computed tomography (SPECT). This test provides several images illustrating the function of the heart muscle. Appropriate segmentation of those images play a crucial role for the diagnosis of heart disease. Consequently, this paper proposes a segmentation method for 2D myocardial perfusion SPECT images acquired in both stress and rest cases. In this way, an expert can make visual assessment of the changes in the stress and rest images easily. Hence, possible heart diseases would be identified based on those changes without a need of using polar maps or reference databases.
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Schedule a callMore From: Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering
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