Abstract
First pass perfusion cardiac magnetic resonance imaging (FPP-CMR) presents a non-invasive method of detecting restricted blood flow to the myocardium, heart muscle tissue, early in development of coronary heart disease. This paper proposes simple classification methods applied to FPP-CMR data to detect regions of poor perfusion. Preliminary results show correspondence to regions of scar tissue detected from thresholding of late Gadolinium enhancement CMR imaging.
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References
Patel, M., et al.: Low Diagnostic Yield of Elective Coronary Angiography. New England Journal of Medicine (March 2010)
Heiberg, E., et al.: Design and validation of Segment–freely available software for cardiovascular image analysis. BMC Med. Imaging 10(1) (January 11, 2010), doi:10.1186/1471-2342-10-1. NOTE: Analysis was performed using Segment version 1.9 R2046 ( http://segment.heiberg.se )
Gebker, R., Schwitter, J., Fleck, E., Nagel, E.: How We Perform Myocardial Perfusion With Cardiovascular Magnetic Resonance. Journal of Cardiovascular Magnetic Resonance (2007)
Kim, R., Shah, D., Judd, R.: How We Perform Delay Enhancement Imaging. Journal of Cardiovascular Magnetic Resonance (2003)
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© 2014 Springer International Publishing Switzerland
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Kruzick, S., Mengshoel, O., Menon, P.G. (2014). Detection of Myocardial Perfusion Defects Using First Pass Perfusion Cardiac MRI Data. In: Zhang, Y.J., Tavares, J.M.R.S. (eds) Computational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications. CompIMAGE 2014. Lecture Notes in Computer Science, vol 8641. Springer, Cham. https://doi.org/10.1007/978-3-319-09994-1_23
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DOI: https://doi.org/10.1007/978-3-319-09994-1_23
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09993-4
Online ISBN: 978-3-319-09994-1
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