Quantitative single point imaging with compressed sensing

Article (PDF Available)inJournal of Magnetic Resonance 201(1):72-80 · September 2009with51 Reads
DOI: 10.1016/j.jmr.2009.08.003 · Source: PubMed
Abstract
A novel approach with respect to single point imaging (SPI), compressed sensing, is presented here that is shown to significantly reduce the loss of accuracy of reconstructed images from under-sampled acquisition data. SPI complements compressed sensing extremely well as it allows unconstrained selection of sampling trajectories. Dynamic processes featuring short T2* NMR signal can thus be more rapidly imaged, in our case the absorption of moisture by a cereal-based wafer material, with minimal loss of image quantification. The absolute moisture content distribution is recovered via a series of images acquired with variable phase encoding times allowing extrapolation to time zero for each image pixel and the effective removal of T2* contrast.
    • "Due to their robustness in the presence of paramagnetic impurities and magnetic susceptibility gradients, the pure phase encode methods have proven to be suitable for providing quantitative measurements of the fluid content in particularly challenging systems, such as rock cores. Single point imaging (SPI) with CS has been employed to quantitatively 3D-image dynamic moisture absorption processes within cereal-based wafer material [45]. Under-sampling the acquisition (at 33 % of k-space) reduced the acquisition time from 39 to 13 min. "
    [Show abstract] [Hide abstract] ABSTRACT: Three-dimensional (3D) imaging of the fluid distributions within the rock is essential to enable the unambiguous interpretation of core flooding data. Magnetic resonance imaging (MRI) has been widely used to image fluid saturation in rock cores; however, conventional acquisition strategies are typically too slow to capture the dynamic nature of the displacement processes that are of interest. Using Compressed Sensing (CS), it is possible to reconstruct a near-perfect image from significantly fewer measurements than was previously thought necessary, and this can result in a significant reduction in the image acquisition times. In the present study, a method using the Rapid Acquisition with Relaxation Enhancement (RARE) pulse sequence with CS to provide 3D images of the fluid saturation in rock core samples during laboratory core floods is demonstrated. An objective method using image quality metrics for the determination of the most suitable regularisation functional to be used in the CS reconstructions is reported. It is shown that for the present application, Total Variation outperforms the Haar and Daubechies3 wavelet families in terms of the agreement of their respective CS reconstructions with a fully-sampled reference image. Using the CS-RARE approach, 3D images of the fluid saturation in the rock core have been acquired in 16 minutes. The CS-RARE technique has been applied to image the residual water saturation in the rock during a water-water displacement core flood. With a flow rate corresponding to an interstitial velocity of vi=1.89±0.03ftday-1, 0.1 pore volumes were injected over the course of each image acquisition, a four-fold reduction when compared to a fully-sampled RARE acquisition. Finally, the 3D CS-RARE technique has been used to image the drainage of dodecane into the water-saturated rock in which the dynamics of the coalescence of discrete clusters of the non-wetting phase are clearly observed. The enhancement in the temporal resolution that has been achieved using the CS-RARE approach enables dynamic transport processes pertinent to laboratory core floods to be investigated in 3D on a time-scale and with a spatial resolution that, until now, has not been possible.
    Full-text · Article · Jul 2016
    • "Many NMR spectra for example are ideally suited to CS reconstruction, as they consist of relatively few isolated peaks in the Fourier basis, and therefore are inherently sparse. The combinations of CS with reconstruction techniques that exploit prior knowledge of the signal allow sampling of down to $1/6 of k-space910111213. While these developments are very significant for rapid MRI, it is also of interest to minimize the sampling of k-space further and avoid Fourier transforming k-space all together to obtain essential signal density statistics. "
    Full-text · Dataset · Feb 2015 · Journal of Magnetic Resonance
    • "Many NMR spectra for example are ideally suited to CS reconstruction, as they consist of relatively few isolated peaks in the Fourier basis, and therefore are inherently sparse. The combinations of CS with reconstruction techniques that exploit prior knowledge of the signal allow sampling of down to $1/6 of k-space910111213. While these developments are very significant for rapid MRI, it is also of interest to minimize the sampling of k-space further and avoid Fourier transforming k-space all together to obtain essential signal density statistics. "
    [Show abstract] [Hide abstract] ABSTRACT: We demonstrate a method to manipulate magnetic resonance data such that the moments of the signal spatial distribution are readily accessible. Usually, magnetic resonance imaging relies on data acquired in so-called k-space which is subsequently Fourier transformed to render an image. Here, via analysis of the complex signal in the vicinity of the centre of k-space we are able to access the first three moments of the signal spatial distribution, ultimately in multiple directions. This is demonstrated for biofouling of a reverse osmosis (RO) membrane module, rendering unique information and an early warning of the onset of fouling. The analysis is particularly applicable for the use of mobile magnetic resonance spectrometers; here we demonstrate it using an Earth's magnetic field system. Copyright © 2015 Elsevier Inc. All rights reserved.
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