Undersampled linogram trajectory for fast imaging (ULTI): experiments at 3 T and 7 T

Abstract

In this study, the performance of linogram acquisition was investigated for the reconstruction of images from undersampled data using parallel imaging methods. The point spread function (PSF) of linogram sampling was analyzed for image sharpness and artifacts. Generalized auto-calibrating partially parallel acquisition was implemented for this new sampling scheme, and images were reconstructed with high acceleration rates. The results were compared with conventional radial sampling methods using simulations and phantom experiments at 3 T. Additionally, a human volunteer was scanned at 7 T. The results demonstrated that the PSF was sharper and the mean artifact power was lower for linogram sampling compared with radial sampling. Results of simulations and phantom experiments were in accord with the findings of the PSF analysis. In simulations, errors in the reconstructed images were lower for linogram sampling. In phantom experiments, fine details and sharp edges were preserved for linogram sampling, while details were blurred for radial sampling. The in vivo human study demonstrated that linogram sampling could provide high quality images of anatomy, even at high acceleration rates. Linogram sampling not only possesses the advantages of radial sampling, such as reduced sensitivity to motion and higher acceleration rates, but it also provides sharper images with fewer artifacts. Moreover, it is less prone to off-resonance artifacts compared with radial sampling. Copyright © 2016 John Wiley & Sons, Ltd.

The discrete Fourier transform for golden angle linogram sampling

“…However, linograms have never been brought into this context and the idea of joining golden angle (or more general) angular distributions with linogram-based [5][6][7] sampling is new to the present work. Not only does it result in computationally effective methods, as we extensively discuss in this paper, but the wider coverage of the Fourier space of linograms compared to polar domains has recently been shown to bring improvements in image quality as well [8,9]. Our contribution here is, therefore, twofold.…”

“…We now present our upper bound for the approximation error due to the truncation (10). (6), τ I as in (8), and D I,N L ,S (θ) as in (10) with (11), then…”

“…• The computational cost of the method scales linearly with the length of the truncated sum; other known methods scale with the square of this length 8 . • Parallelization of the method is efficient and its memory access pattern is cache-friendly.…”

Comparison of MRI Under-Sampling Techniques for Compressed Sensing with Translation Invariant Wavelets Using FastTestCS: A Flexible Simulation Tool

“…Finally, Section 5 discusses these results with the use of FastTestCS. analyze a Cartesian based radial sampling trajectory for MRI [17]. In many of these cases, due to computational simplicity, the Fast Fourier Transform (FFT) is desired, which operates on a Cartesian grid.…”