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© Springer International Publishing Switzerland 2016. Quantitative perfusion assessment using magnetic resonance imaging (MRI) is one of the methods used in Coronary Artery Disease (CAD) diagnosis. In this study we investigated the possibility of performing perfusion quantification using Fermi function modeling on the data acquired in the way typical for visual perfusion assessment with high dose of contrast agent. 25 patients with CAD symptoms have been examined by MRI in stress and rest condition. Image processing and numerical model have been implemented to quantify myocardial perfusion reserve (MPR). The results have been compared with the visual perfusion reserve qualification by an experienced physician. Accuracy of quantitative method in classification perfusion in myocardial segments was below 80%, meaning this method in this setup is not yet ready for clinical applications.

Original publication

DOI

10.1007/978-3-319-23923-1_15

Type

Chapter

Book title

Advances in Intelligent Systems and Computing

Publication Date

01/01/2016

Volume

393

Pages

105 - 110