Title :
Myocardial Blood Flow Quantification From MRI by Deconvolution Using an Exponential Approximation Basis
Author :
Hautvast, Gilion ; Chiribiri, Amedeo ; Zarinabad, Niloufar ; Schuster, Andreas ; Breeuwer, Marcel ; Nagel, Eike
Author_Institution :
Imaging Syst. - MR, Philips Healthcare, Best, Netherlands
fDate :
7/1/2012 12:00:00 AM
Abstract :
We have evaluated the use of deconvolution using an exponential approximation basis for the quantification of myocardial blood flow from perfusion cardiovascular magnetic resonance. Our experiments, based on simulated signal intensity curves, phantom acquisitions, and clinical image data, indicate that exponential deconvolution allows for accurate quantification of myocardial blood flow. Together with automated respiratory motion correction myocardial contour delineation, the exponential deconvolution enables efficient and reproducible quantification of myocardial blood flow in clinical routine.
Keywords :
biomedical MRI; cardiovascular system; deconvolution; exponential distribution; haemodynamics; haemorheology; image registration; medical image processing; phantoms; MRI; clinical image data; exponential approximation basis; exponential deconvolution; image registration; myocardial blood flow quantification; perfusion cardiovascular magnetic resonance; phantom acquisitions; simulated signal intensity curves; Deconvolution; Dynamics; Equations; Mathematical model; Myocardium; Phantoms; Silicon; Deconvolution; myocardial perfusion; validation; Algorithms; Coronary Circulation; Hemodynamics; Image Processing, Computer-Assisted; Magnetic Resonance Angiography; Models, Cardiovascular; Phantoms, Imaging;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2012.2197620