F. T. A. W. Wajer

Reconstruction of MRI Images from Non-Uniform Sampling and Its Application to Intrascan Motion Correction in Functional MRI

Motion constitutes a perennial problem in Magnetic Resonance Imaging (MRI). It leads to artifacts in the images. In functional MRI (fMRI), motion is also a major limitation to accurate detection of neuronal activity.

Dynamic MR-imaging with radial scanning, a post-acquisition keyhole approach

A new method for 2D/3D dynamic MR-Imaging with radial scanning is proposed. It exploits the inherent strong oversampling in the centre of-space, which holds crucial temporal information of the contrast evolution. It is based on (1) a rearrangement of (novel 3D) isotropic distributions of trajectories during the scan according to the desired time resolution and (2) a post-acquisition keyhole approach. The 2D/3D dynamic images are reconstructed using 2D/3D-gridding and 2D/3D-IFFT. The scan time is not increased with respect to a conventional 2D/3D radial scan of the same image resolution, in addition one benefits from the dynamic information. An application to in vivo ventilation of rat lungs using hyperpolarized helium is demonstrated.

Dynamic magnetic resonance imaging with radial scanning: a post-acquisition keyhole approach

A method—PA-keyhole—for 2D/3D dynamic magnetic resonance imaging with radial scanning is proposed. PA-keyhole exploits the inherent strong oversampling in the center of k-space, which contains crucial temporal information regarding contrast evolution. The method is based on: (1) a rearrangement of the temporal order of 2D/3D isotropic distributions of trajectories during the scan into subdistributions according to the desired time resolution, (2) a new post-acquisition keyhole approach based on the replacement of the central disk/sphere in k-space using data solely from a subdistribution, and (3) reconstruction of 2D/3D dynamic (time-resolved) images using 2D/3D-gridding with Pipes approach to the sampling density compensation and 2D/3D-IFFT. The scan time is not increased with respect to a conventional 2D/3D radial scan of the same spatial resolution; in addition, one benefits from the dynamic information. The abilities of PA-keyhole and the sliding window techniques to restore simulated dynamic contrast changes are compared. Results are shown both for 2D and 3D dynamic imaging using experimental data. An application to in-vivo ventilation of rat lungs using hyperpolarized helium is demonstrated.

Retrospective intra-scan motion correction

This paper analyzes the effects of intra-scan motion and demonstrates the possibility of correcting them directly in k-space with a new automatic retrospective method. The method is presented for series of 2D acquisitions with Cartesian sampling. Using a reference k-space acquisition (corrected for translations) within the series, intra-scan motion parameters are accurately estimated for each trajectory in k-space of each data set in the series resulting in pseudo-random sample positions. The images are reconstructed with a Bayesian estimator that can handle sparse arbitrary sampling in k-space and reduces intra-scan rotation artefacts to the noise level. The method has been assessed by means of a Monte Carlo study on axial brain images for different signal-to-noise ratios. The accuracy of motion estimates is better than 0.1 degrees for rotation, and 0.1 and 0.05 pixel, respectively, for translation along the read and phase directions for signal-to-noise ratios higher than 6 of the signals on each trajectory. An example of reconstruction from experimental data corrupted by head motion is also given.

Nonuniform sampling in magnetic resonance imaging

This paper concerns reconstruction of MR images from raw, nonuniformly sampled k-space data. The exposed methods are (1) gridding, which resamples to a uniform rectangular grid and works well in the absence of undersampling; and (2) Bayesian estimation, which can accommodate undersampling.

Influence of digital audio filters on image reconstruction in MRI

This paper deals with the influence of the transient response and group delay of digital filters on the MRI signal and its aspects in image reconstruction. The consequence of digital filtration on the acquired signal will be shown in the time domain (k-space) for three basic imaging methods-echo scan, radial scan and spiral scan. The influence of the group delay and transient response of filters will be explained and a method will be proposed which compensates both these phenomena while retaining all the advantages of digital filtration. The proposed method is based on applying the principle of signal superposition and on using the consequences of the sampling principle. The method works in the time domain. It is very simple and rapid and does not depend on the properties of the acquired signal or reconstruction algorithm. It will be shown and explained in which cases the transient response can be neglected and in which it has to be compensated. In the end, the results of the proposed methods will be shown for mentioned cases on a simulated signal in the image domain.

MR image reconstruction algorithms for sparse k-space data: a Java-based integration.

We have worked on multi-dimensional magnetic resonance imaging (MRI) data acquisition and related image reconstruction methods that aim at reducing the MRI scan time. To achieve this scan-time reduction we have combined the approach of ’increasing the speed’ ofk-space acquisition with that of ‘deliberately omitting’ acquisition ofk-space trajectories (sparse sampling). Today we have a whole range of (sparse) sampling distributions and related reconstruction methods. In the context of a European Union Training and Mobility of Researchers project we have decided to integrate all methods into one coordinating software system. This system meets the requirements that it is highly structured in an object-oriented manner using the Unified Modeling Language and the Java programming environment, that it uses the client-server approach, that it allows multi-client communication sessions with facilities for sharing data and that it is a true distributed computing system with guaranteed reliability using core activities of the Java Jini package.

Magnetic Resonance Image Reconstruction from Nonuniformly Sampled k-space Data

Medical doctors exert perennial pressure on scanner manufacturers to reduce the measurement time of Magnetic Resonance Imaging (MRI). Applications requiring measurement time reduction are, among others, real-time imaging of the heart, bolus tracking, contrast-agent uptake, and functional imaging. To achieve this goal, one can either devise faster measurement techniques or skip substantial numbers of sample points, or both. Often, the adopted tactics amount to nonuniform undersampling. Unfortunately, this complicates reconstruction of the MR image.

SVD-Based modelling of medical NMR signals

Publisher Summary A Magnetic Resonance (MR) scanner enables one to noninvasively detect and quantify biochemical substances at selected positions in patients. The MR signal detected by the scanner comprises a number of damped sinusoids in the time domain. Each chemical substance contributes at least one sinusoid, at a specific frequency. Often, metabolite quantification is severely hampered by interference with strong MR signals of water and other substances (for example fat) resident in the human body. The damping function of the interfering sinusoids is nonexponential, which aggravates the situation. This chapter investigates subtraction of interfering sinusoids by means of SVD-based state space modeling. Among other things, modeling of all details of the signal is attempted (zero-error-modeling) in the chapter. It also provides rank criteria for three alternative Hankel data matrices guaranteeing zero-error-modeling and discusses measures to be proposed and tested on simulated signals in order to meet the criteria. The chapter concludes with the observation that, although zero-error-modeling can indeed be achieved, it turns out that such modeling does not guarantee exact separation of the unwanted sinusoids from the wanted sinusoids.