A hybrid method for more efficient channel-by-channel reconstruction with many channels.

In MRI, imaging using receiving coil arrays with a large number of elements is an area of growing interest. With increasing channel numbers for parallel acquisition, longer reconstruction times have become a significant concern. Channel reduction techniques have been proposed to reduce the processing time of channel-by-channel reconstruction algorithms. In this article, two schemes are combined to enable faster and more accurate reconstruction than existing channel reduction techniques. One scheme use two stages of channel reduction instead of one. The other scheme is to incorporate all acquired data into the final reconstruction. The combination of these two schemes is called flexible virtual coil. Applications of flexible virtual coil for partially parallel imaging, motion compensation, and compressed sensing are presented as specific examples. Theoretical analysis and experimental results demonstrate that the proposed method has a major impact in reducing computation cost in reconstruction with high-channel count coil elements.

High temporal resolution retrospective motion correction with radial parallel imaging.

A method for motion correction in multicoil imaging applications, involving both data collection and reconstruction, is presented. A bit-reversed radial acquisition scheme, in conjunction with a rapid self-calibrated parallel imaging method, Generalized auto-calibrating partial parallel acquisition (GRAPPA) operator for wider radial bands (GROWL), is used to achieve motion correction at a high temporal resolution. View-by-view in-plane motion correction is achieved in 2D imaging, while 3D motion correction is achieved for every two consecutive slice-encoding planes in 3D imaging. In the proposed technique, GROWL contributes in two aspects: First, a central k-space circle/cylinder used as the motion-free reference is generated from a small number of radial lines/planes; Second, undersampled k-space regions resulting from rotation and inconsistent (e.g. intraview and nonrigid body) motion can be filled in. When compared with navigator-based motion correction methods, the proposed method does not prolong scan time and can be applied to short-TR sequences. Magn Reson Med, 2011. © 2011 Wiley-Liss, Inc.

K-t sparse GROWL: sequential combination of partially parallel imaging and compressed sensing in k-t space using flexible virtual coil.

Because dynamic MR images are often sparse in x-f domain, k-t space compressed sensing (k-t CS) has been proposed for highly accelerated dynamic MRI. When a multichannel coil is used for acquisition, the combination of partially parallel imaging and k-t CS can improve the accuracy of reconstruction. In this work, an efficient combination method is presented, which is called k-t sparse Generalized GRAPPA fOr Wider readout Line. One fundamental aspect of this work is to apply partially parallel imaging and k-t CS sequentially. A partially parallel imaging technique using a Generalized GRAPPA fOr Wider readout Line operator is adopted before k-t CS reconstruction to decrease the reduction factor in a computationally efficient way while preserving temporal resolution. Channel combination and relative sensitivity maps are used in the flexible virtual coil scheme to alleviate the k-t CS computational load with increasing number of channels. Using k-t FOCUSS as a specific example of k-t CS, the experiments with Cartesian and radial data sets demonstrate that k-t sparse Generalized GRAPPA fOr Wider readout Line can produce results with two times lower root-mean-square error than conventional channel-by-channel k-t CS while consuming up to seven times less computational cost.

Off-resonance artifacts correction with convolution in k-space (ORACLE).

Off-resonance artifacts hinder the wider applicability of echo-planar imaging and non-Cartesian MRI methods such as radial and spiral. In this work, a general and rapid method is proposed for off-resonance artifacts correction based on data convolution in k-space. The acquired k-space is divided into multiple segments based on their acquisition times. Off-resonance-induced artifact within each segment is removed by applying a convolution kernel, which is the Fourier transform of an off-resonance correcting spatial phase modulation term. The field map is determined from the inverse Fourier transform of a basis kernel, which is calibrated from data fitting in k-space. The technique was demonstrated in phantom and in vivo studies for radial, spiral and echo-planar imaging datasets. For radial acquisitions, the proposed method allows the self-calibration of the field map from the imaging data, when an alternating view-angle ordering scheme is used. An additional advantage for off-resonance artifacts correction based on data convolution in k-space is the reusability of convolution kernels to images acquired with the same sequence but different contrasts.

Generalized GRAPPA operators for wider spiral bands: rapid self-calibrated parallel reconstruction for variable density spiral MRI.

A rapid and self-calibrated parallel imaging reconstruction method is proposed for undersampled variable density spiral datasets. A set of generalized GRAPPA for wider readout line operators are used to expand each acquired spiral line into a wider spiral band, therefore fulfilling Nyquist sampling criterion throughout the k-space. The calibration of generalized GRAPPA for wider readout line operators is performed using the fully sampled central k-space region. The resulting generalized GRAPPA for wider readout line operator weights are adaptively regularized to minimize the error in the newly-generated data at different k-space locations. Simulation and experimental results demonstrate that the technique can be used either to achieve a significant acceleration and/or to reduce off-resonance artifacts due to a shorten readout duration.

GRAPPA operator for wider radial bands (GROWL) with optimally regularized self-calibration.

A self-calibrated parallel imaging reconstruction method is proposed for azimuthally undersampled radial dataset. A generalized auto-calibrating partially parallel acquisition (GRAPPA) operator is used to widen each radial view into a band consisting of several parallel lines, followed by a standard regridding procedure. Self-calibration is achieved by regridding the central k-space region, where Nyquist criterion is satisfied, to a rotated Cartesian grid. During the calibration process, an optimal Tikhonov regularization factor is introduced to reduce the error caused by the small k-space area of the self-calibration region. The method was applied to phantom and in vivo datasets acquired with an eight-element coil array, using 32-64 radial views with 256 readout samples. When compared with previous radial parallel imaging techniques, GRAPPA operator for wider radial bands (GROWL) provides a significant speed advantage since calibration is carried out using the fully sampled k-space center. A further advantage of GROWL is its applicability to arbitrary-view angle ordering schemes.

Data convolution and combination operation (COCOA) for motion ghost artifacts reduction.

A novel method, data convolution and combination operation, is introduced for the reduction of ghost artifacts due to motion or flow during data acquisition. Since neighboring k-space data points from different coil elements have strong correlations, a new "synthetic" k-space with dispersed motion artifacts can be generated through convolution for each coil. The corresponding convolution kernel can be self-calibrated using the acquired k-space data. The synthetic and the acquired data sets can be checked for consistency to identify k-space areas that are motion corrupted. Subsequently, these two data sets can be combined appropriately to produce a k-space data set showing a reduced level of motion induced error. If the acquired k-space contains isolated error, the error can be completely eliminated through data convolution and combination operation. If the acquired k-space data contain widespread errors, the application of the convolution also significantly reduces the overall error. Results with simulated and in vivo data demonstrate that this self-calibrated method robustly reduces ghost artifacts due to swallowing, breathing, or blood flow, with a minimum impact on the image signal-to-noise ratio.

Motion correction using an enhanced floating navigator and GRAPPA operations.

A method for motion correction in multicoil imaging applications, involving both data collection and reconstruction, is presented. The floating navigator method, which acquires a readout line off center in the phase-encoding direction, is expanded to detect translation/rotation and inconsistent motion. This is done by comparing floating navigator data with a reference k-space region surrounding the floating navigator line, using a correlation measure. The technique of generalized autocalibrating partially parallel acquisition is further developed to correct for a fully sampled, motion-corrupted dataset. The flexibility of generalized autocalibrating partially parallel acquisition kernels is exploited by extrapolating readout lines to fill in missing "pie slices" of k-space caused by rotational motion and regenerating full k-space data from multiple interleaved datasets, facilitating subsequent rigid-body motion correction or proper weighting of inconsistent data (e.g., with through-plane and nonrigid motion). Phantom and in vivo imaging experiments with turbo spin-echo sequence demonstrate the correction of severe motion artifacts.

A rapid and robust numerical algorithm for sensitivity encoding with sparsity constraints: self-feeding sparse SENSE.

The method of enforcing sparsity during magnetic resonance imaging reconstruction has been successfully applied to partially parallel imaging (PPI) techniques to reduce noise and artifact levels and hence to achieve even higher acceleration factors. However, there are two major problems in the existing sparsity-constrained PPI techniques: speed and robustness. By introducing an auxiliary variable and decomposing the original minimization problem into two subproblems that are much easier to solve, a fast and robust numerical algorithm for sparsity-constrained PPI technique is developed in this work. The specific implementation for a conventional Cartesian trajectory data set is named self-feeding Sparse Sensitivity Encoding (SENSE). The computational cost for the proposed method is two conventional SENSE reconstructions plus one spatially adaptive image denoising procedure. With reconstruction time approximately doubled, images with a much lower root mean square error (RMSE) can be achieved at high acceleration factors. Using a standard eight-channel head coil, a net acceleration factor of 5 along one dimension can be achieved with low RMSE. Furthermore, the algorithm is insensitive to the choice of parameters. This work improves the clinical applicability of SENSE at high acceleration factors.

MR Imaging of the Newborn: a technical perspective.

This article discusses neonatal magnetic resonance (MR) imaging and reviews equipment and procedures for MR-related transport, sedation, monitoring, and scanning. MR is gaining importance in the diagnosis and clinical management of critically ill, and often very low birth weight infants, so research is ongoing to make transport and examination safer and imaging more successful. Efforts are focused on integration of dedicated neonate MR scanners in neonatal intensive care units, improvements in incubator technology and handling, and more efficient use of scan/sedation time by choosing dedicated neonate coil arrays that improve the signal-to-noise-ratio and facilitate the choice of modern imaging techniques.

Active device tracking and high-resolution intravascular MRI using a novel catheter-based, opposed-solenoid phased array coil.

A novel two-element, catheter-based phased array coil was designed and built for both active MR device tracking and high-resolution vessel wall imaging. The device consists of two independent solenoid coils that are wound in opposite directions, connected to separate receive channels, and mounted collinearly on an angiographic catheter. The elements were used independently or together for tracking or imaging applications, respectively. The array's dual functionality was tested on a clinical 1.5 T MRI scanner in vitro, in vivo, and in situ. During real-time catheter tracking, each element gave rise to a high-amplitude peak in the respective projection data, which enabled reliable and robust device tracking as well as automated slice positioning. In vivo microimaging with 240 microm in-plane resolution was achieved in 9 s using the device and TrueFISP imaging. Therefore, a single device was successfully implemented that met the combined requirements of intravascular device tracking and imaging.