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

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...

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Hauptverfasser: Delles, M., Rengier, F., Ley, S., von Tengg-Kobligk, H., Kauczor, H., Dillmann, R., Unterhinninghofen, R.
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container_start_page 6829
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creator Delles, M.
Rengier, F.
Ley, S.
von Tengg-Kobligk, H.
Kauczor, H.
Dillmann, R.
Unterhinninghofen, R.
description 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.
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Algorithms
Biomedical imaging
Blood
Blood Flow Velocity - physiology
Blood Pressure
Humans
Image Processing, Computer-Assisted
Imaging, Three-Dimensional - methods
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Models, Statistical
Models, Theoretical
Noise
Phantoms, Imaging
Polynomials
Reference Values
Reproducibility of Results
Signal Processing, Computer-Assisted
Time Factors
Velocity measurement
title Polynomial regularization for robust MRI-based estimation of blood flow velocities and pressure gradients
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