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Type: Journal article
Title: Theory and validation of magnetic resonance fluid motion estimation using intensity flow data
Author: Wong, K.
Kelso, R.
Worthley, S.
Sanders, P.
Mazumdar, J.
Abbott, D.
Citation: PLoS One, 2009; 4(3):e1-e15
Publisher: Public Library of Science
Issue Date: 2009
ISSN: 1932-6203
Statement of
Kelvin Kian Loong Wong, Richard Malcolm Kelso, Stephen Grant Worthley, Prashanthan Sanders, Jagannath Mazumdar, Derek Abbott
Abstract: Background Motion tracking based on spatial-temporal radio-frequency signals from the pixel representation of magnetic resonance (MR) imaging of a non-stationary fluid is able to provide two dimensional vector field maps. This supports the underlying fundamentals of magnetic resonance fluid motion estimation and generates a new methodology for flow measurement that is based on registration of nuclear signals from moving hydrogen nuclei in fluid. However, there is a need to validate the computational aspect of the approach by using velocity flow field data that we will assume as the true reference information or ground truth. Methodology/Principal Findings In this study, we create flow vectors based on an ideal analytical vortex, and generate artificial signal-motion image data to verify our computational approach. The analytical and computed flow fields are compared to provide an error estimate of our methodology. The comparison shows that the fluid motion estimation approach using simulated MR data is accurate and robust enough for flow field mapping. To verify our methodology, we have tested the computational configuration on magnetic resonance images of cardiac blood and proved that the theory of magnetic resonance fluid motion estimation can be applicable practically. Conclusions/Significance The results of this work will allow us to progress further in the investigation of fluid motion prediction based on imaging modalities that do not require velocity encoding. This article describes a novel theory of motion estimation based on magnetic resonating blood, which may be directly applied to cardiac flow imaging.
Keywords: Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging; Magnetic Resonance Spectroscopy; Computer Simulation; Models, Theoretical; Algorithms
Description: 15 p.
Rights: Copyright: © 2009 Wong et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
RMID: 0020091432
DOI: 10.1371/journal.pone.0004747
Appears in Collections:Electrical and Electronic Engineering publications

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