DC artifact correction for arbitrary phase-cycling sequence

American Journal of Biomedical Engineering, 2016

MRI machine one of the most significant diagnostic modalities. The only restriction that affects the MRI image is that imaging procedure take very long time comparing with CT scan and other diagnostic modalities, thus old patient, children and the illness people cannot stay without movement inside the magnet therefore artifact (phase mismaping artifact) will affect the MRI image and several miss analysis may occur especially in the neuroanatomical measurements. Many procedure has been use to solve this problem for example before during and after the MRI image reconstruction. In this study the effectiveness of a new retrospective motion correction technique has been applied and tested. Three different section MRI image (coronal, sagittal and axial) were used and given different correction results. That was by develop algorithm to correct the motion blur in the MRI image that corrupted by patient rigid motion. Wiener filter was used as the main restoration procedure by means of angle ...

Magnetic Resonance in Medicine, 2018

Purpose-Background phase offsets (BPO) in phase contrast (PC) MRI are often corrected using polynomial regression; however, correction performance degrades when temporally-invariant outliers such as steady flow or spatial wrap-around artifact are present. We describe and validate an iterative method, called Automatic Rejection of Temporally-invariant Outliers (ARTO), that excludes these outliers from the fitting process. Theory and Methods-ARTO iteratively removes pixels with large polynomial regression errors analyzed by a Gaussian mixture model fitting of the residual distribution. One-hundred-fifty trials of a simulated phantom (75 with wrap-around artifact) and 125 PC-MRI cines from 22 healthy subjects (48 with wrap-around artifact) were used for validation. BPO offsets were corrected using 2 nd order weighted regularized least squares (WRLS) with and without ARTO. Flow volumes after WRLS and WRLS+ARTO corrections were compared to the known truth (phantom) and stationary phantom reference (in vivo) using Bland-Altman analysis. Qp/Qs ratio was also computed in a subset of 6 subjects. Results-In the simulated phantom, compared to WRLS and no-correction, correction with WRLS+ARTO produced superior agreement in volumetric flow quantification with the known truth. In vivo, WRLS+ARTO also produced superior agreement with stationary phantom corrected volumetric flow compared to WRLS and no-correction. In datasets with wrap-around artifact, WRLS produced significantly larger variance in Qp/Qs ratio than stationary phantom correction (P=0.0008). Conclusion-The proposed method provides automatic exclusion of temporally-invariant outliers and produces flow quantification results comparable to stationary phantom correction.

1995

A computer postprocessing technique is developed to remove MRI artifact arising from unknown translational motion in the imaging plane. Based on previous artifact correction methods, the improved technique uses two successive steps to reduce read-out and phase-encoding direction artifacts: First, the spectrum shift method is applied to remove read-out axis translational motion. Then, the phase retrieval method is employed to eliminate the remaining sub-pixel motion of the read-out axis and the entire motion of the phase-encoding axis. In the presence of noise, to protect edge detection (in the spectrum shift method), two high-density gray-level markers are added, one to each side of the imaging object. Experimental results with an actual MR scan conrmed the ability of the method to correct the artifact of an MR image caused by unknown translational motion in the imaging plane.

NeuroImage, 2010

Phase contrast imaging holds great potential for in vivo biodistribution studies of paramagnetic molecules and materials. However, in vivo quantification of iron storage and other paramagnetic materials requires improvements in reconstruction and processing of MR complex images. To achieve this, we have developed a framework including (i) an optimal coil sensitivity smoothing filter for phase imaging determined at the maximal signal to noise ratio, (ii) a phase optimised and a complex image optimised reconstruction approach, and (iii) a magnitude and phase correlation test criterion to determine the low pass filter parameter for background phase removal. The method has been evaluated using 3T and 7T MRI data containing cortical regions, the basal ganglia including the caudate, and the midbrain including the substantia nigra. The optimised reconstruction improves phase image contrast and noise suppression compared with conventional reconstruction approaches, and the correlation test criterion provides an objective method for separation of the local phase signal from the background phase measurements. Phase values of several brain regions of interest have been calculated, including gray matter (− 1.23 Hz at 7T and − 0.55 Hz at 3T), caudate (− 3.8 Hz at 7T), and the substantia nigra (− 6.2 Hz at 7T).

arXiv (Cornell University), 2023

Purpose: Determine the correct mathematical phase description for balanced steady-state free precession (bSSFP) signals in multicompartment systems. Theory and Methods: Based on published bSSFP signal models, two distinct phase descriptions can be formulated: one predicting the presence and the other predicting the absence of destructive interference effects in multicompartment systems. Numerical simulations of bSSFP signals of water and acetone were performed to evaluate the predictions of these two distinct phase descriptions. For experimental validation, bSSFP profiles were measured at 3T using phase-cycled bSSFP acquisitions performed in a phantom containing mixtures of water and acetone, which replicates a system with two signal components. Localized single voxel MRS was performed at 7T to determine the relative chemical-shift of the acetone-water mixtures. Results: Based on the choice of phase description, the simulated bSSFP profiles of water-acetone mixtures varied significantly, either displaying or lacking destructive interference effects, as predicted theoretically. In phantom experiments, destructive interference was consistently observed in the measured bSSFP profiles of wateracetone mixtures, an observation which excludes the phase description that predicts an absence of destructive interference. The connection between the choice of phase description and predicted observation enables an unambiguous experimental identification of the correct phase description for multicompartment bSSFP profiles, which is consistent with Bloch equations. Conclusion: The study emphasizes that consistent phase descriptions are crucial for accurately describing multi-compartment bSSFP signals, as incorrect phase descriptions result in erroneous predictions.

Magnetic Resonance in Medicine, 2014

Purpose: To correct gradient-induced phase errors in radial MRI. Methods: Gradient-induced eddy currents affect the MRI data acquisition by gradient delays and phase errors that may lead to severe image artifacts for non-Cartesian imaging scenarios such as radial trajectories. While gradient delays are dealt with by respective shifts of the acquisition window during radial image acquisition, this work introduces a simple method for quantifying and correcting phase errors from the actual data prior to image reconstruction. For a given gradient system, the approach yields a specific phase error per gradient that can be used for correcting the raw data. Results: Phantom studies at 9.4 T demonstrated marked improvements in radial image quality. It could be shown that the phase correction is not compromised by data undersampling. Moreover, the selective correction of gradient-induced phase errors retained the phase information caused by different concentrations of a paramagnetic contrast agent. Conclusion: The proposed method does not require additional reference measurements and separately corrects for phase errors induced by eddy currents, while retaining the residual phase of the object which may carry physiologic information. Magn Reson Med 71:308-312,

Magnetic Resonance in Medicine, 2003

To characterize gradient field nonuniformity and its effect on velocity encoding in phase contrast (PC) MRI, a generalized model that describes this phenomenon and enables the accurate reconstruction of velocities is presented. In addition to considerable geometric distortions, inhomogeneous gradient fields can introduce deviations from the nominal gradient strength and orientation, and therefore spatially-dependent first gradient moments. Resulting errors in the measured phase shifts used for velocity encoding can therefore cause significant deviations in velocity quantification. The true magnitude and direction of the underlying velocities can be recovered from the phase difference images by a generalized PC velocity reconstruction, which requires the acquisition of full three-directional velocity information. The generalized reconstruction of velocities is applied using a matrix formalism that includes relative gradient field deviations derived from a theoretical model of local gradient field nonuniformity. In addition, an approximate solution for the correction of one-directional velocity encoding is given. Depending on the spatial location of the velocity measurements, errors in velocity magnitude can be as high as 60%, while errors in the velocity encoding direction can be up to 45°. Results of phantom measurements demonstrate that effects of gradient field nonuniformity on PC-MRI can be corrected with the proposed method. Magn Reson Med 50: 791-801,

1996

A post-processing technique has been developed to suppress the MRI artifact arising from object planar rigid motion. In 2-DFT MRI, rotational and translational motions of the target during MR scan respectively impose non-uniform sampling and a phase error on the collected MRI signal. The artifact correction method introduced considers the following three conditions: (i) For planar rigid motion with known parameters, a reconstruction algorithm based on bilinear interpolation and the super-position method is employed to remove the MRI artifact. (ii) For planar rigid motion with known rotation angle and unknown translational motion (including an unknown rotation center), rst, a super-position bilinear interpolation algorithm is used to eliminate artifact due to rotation about the center of the imaging plane, following which a phase correction algorithm is applied to reduce the remaining phase error of the MRI signal. (iii) To estimate unknown parameters of a rigid motion, a minimum energy method is proposed which utilizes the fact that planar rigid motion increases the measured energy of an ideal MR image outside the boundary of the imaging object; by using this property, all unknown parameters of a typical rigid motion are accurately estimated in the presence of noise. To conrm the feasibility of employing the proposed method in a clinical setting, the technique was used to reduce unknown rigid motion artifact arising from the head movements of two volunteers.

IEEE Transactions on Medical Imaging, 2000

A new image reconstruction method to correct for the effects of magnetic field inhomogeneity in non-Cartesian sampled magnetic resonance imaging (MRI) is proposed. The conjugate phase reconstruction method, which corrects for phase accumulation due to applied gradients and magnetic field inhomogeneity, has been commonly used for this case. This can lead to incomplete correction, in part, due to the presence of gradients in the field inhomogeneity function. Based on local distortions to the k-space trajectory from these gradients, a spatially variant sample density compensation function is introduced as part of the conjugate phase reconstruction. This method was applied to both simulated and experimental spiral imaging data and shown to produce more accurate image reconstructions. Two approaches for fast implementation that allow the use of fast Fourier transforms are also described. The proposed method is shown to produce fast and accurate image reconstructions for spiral sampled MRI.

Magnetic Resonance Imaging, 2003

In this paper, we propose a dual image approach to correcting intensity inhomogeneities for MR images acquired using surface coils. Previous methods are usually not satisfactory due to restricted application domains, considerable human interactions, or some undesirable artifacts. The proposed algorithm provides nice correction results for a variety of surface-coil MR images. It is accomplished by using an additional body-coil MR image of a smaller size captured at the same position as that of the surface-coil image to facilitate the estimation of the bias field function. The correction algorithm consists of aligning the surface-coil image with the body-coil image and fitting a spline surface from a sparse set of data points for the associated bias field function. Experiments on some real images show satisfactory correction results by using the proposed algorithm.