NDLI: Polynomial regularization for robust MRI-based estimation of blood flow velocities and pressure gradients

Content Provider	IEEE Xplore Digital Library
Author	Delles, M. Rengier, F. Ley, S. von Tengg-Kobligk, H. Kauczor, H. Dillmann, R. Unterhinninghofen, R.
Copyright Year	2011
Description	Author affiliation: Institute for Anthropomatics, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany (Delles, M.; Dillmann, R.; Unterhinninghofen, R.) \|\| Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, 69120 Heidelberg, Germany (Rengier, F.; Ley, S.; von Tengg-Kobligk, H.; Kauczor, H.)
Abstract	In cardiovascular diagnostics, phase-contrast MRI is a valuable technique for measuring blood flow velocities and computing blood pressure values. Unfortunately, both velocity and pressure data typically suffer from the strong image noise of velocity-encoded MRI. In the past, separate approaches of regularization with physical a-priori knowledge and data representation with continuous functions have been proposed to overcome these drawbacks. In this article, we investigate polynomial regularization as an exemplary specification of combining these two techniques. We perform time-resolved three-dimensional velocity measurements and pressure gradient computations on MRI acquisitions of steady flow in a physical phantom. Results based on the higher quality temporal mean data are used as a reference. Thereby, we investigate the performance of our approach of polynomial regularization, which reduces the root mean squared errors to the reference data by 45% for velocities and 60% for pressure gradients.
Starting Page	6829
Ending Page	6832
File Size	798139
Page Count	4
File Format	PDF
ISBN	9781424441211
ISSN	1557170X
e-ISBN	9781457715891
e-ISBN	9781424441228
DOI	10.1109/IEMBS.2011.6091684
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Polynomials Magnetic resonance imaging Biomedical imaging Velocity measurement Noise Blood
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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