Referenceless one-dimensional Nyquist ghost correction in multicoil single-shot spatiotemporally encoded MRI

Single-shot spatiotemporally encoded (SPEN) MRI is a novel fast imaging method capable of retaining the time efficiency of single-shot echo planar imaging (EPI) but with distortion artifacts significantly reduced. Akin to EPI, the phase inconsistencies between mismatched even and odd echoes also result in the so-called Nyquist ghosts. However, the characteristic of the SPEN signals provides the possibility of obtaining ghost-free images directly from even and odd echoes respectively, without acquiring additional reference scans. In this paper, a theoretical analysis of the Nyquist ghosts manifested in single-shot SPEN MRI is presented, a one-dimensional correction scheme is put forward capable of maintaining definition of image features without blurring when the phase inconsistency along SPEN encoding direction is negligible, and a technique is introduced for convenient and robust correction of data from multi-channel receiver coils. The effectiveness of the proposed processing pipeline is validated by a series of experiments conducted on simulation data, in vivo rats and healthy human brains. The robustness of the method is further verified by implementing distortion correction on ghost corrected data.     

Image-Based Reduction of Artifacts in Multishot Echo-Planar Imaging

The method to reduce the ghost artifact in echo-planar imaging (EPI) using a phase correction derived from the image data (M. H. Buonocore and L. Gao,Magn. Reson. Med.38, 89 (1997)) is generalized to multishot (interleaved) EPI, where the artifact takes the form of multiple ghosts. The method is shown to be much more sensitive to noise when applied to standard interleaved data than is the case with single-shot EPI, because the calculation must be based on high-order ghosts of low intensity. A modified interleaving scheme is proposed for multishot EPI in which the initial trajectory direction alternates in consecutive shots and the number of shots is odd. With this scheme, only a single ghost shifted by one-half of the field of view appears just as in the single-shot EPI, and the image-based phase correction can be applied with the usual sensitivity to noise.     

High-resolution diffusion imaging using phase-corrected segmented echo-planar imaging

Diffusion magnetic resonance imaging (MRI) was performed with a high-resolution segmented echo-planar imaging technique, which provided images with substantially less susceptibility artifacts than images obtained with single-shot echo-planar imaging (EPI). Diffusion imaging performed with any multishot pulse sequence is inherently sensitive to motion artifacts and in order to reduce motion artifacts, the presented method utilizes navigator echo phase corrections, performed after a one-dimensional Fourier transform along the frequency-encoding direction. Navigator echo phases were fitted to a straight line prior to phase correction to avoid errors from internal motion. In vivo imaging was performed using electro cardiographic (ECG) triggering. Apparent diffusion coefficient (ADC) maps were calculated on a pixel-by-pixel basis using up to seven diffusion sensitivities, ranging from b = 0 to 1129 x 10(6) s/m(2).     

Improved B0 field map estimation for high field EPI

Echo planar imaging (EPI) is an ultrafast magnetic resonance imaging (MRI) technique that allows one to acquire a 2D image in about 100 ms. Unfortunately, the standard EPI images suffer from substantial geometric distortions, mainly originating from susceptibility differences in adjacent tissues. To reduce EPI distortions, correction methods based on a field map, which is a map of the off-resonance frequencies, have been developed. In this work, a nonlinear least squares estimator is used to optimize the estimation of the field map of the B₀ field. The model of the EPI and reference data includes parameters for the phase evolution, the complex magnitude, the relaxation of the MRI signal and the EPI-specific phase difference between odd and even echoes, and from these parameters, additional corrections might be computed. The reference data required to estimate the field map can be acquired with a modified EPI-sequence. The proposed method is tested on simulated as well as experimental data and proves to be significantly more robust against noise, compared to the previously suggested method.     

Motion artifact suppression: a review of post-processing techniques.

Patient motion during data acquisition in magnetic resonance imaging causes artifacts in the reconstructed image, which for two-dimensional Fourier transform imaging techniques appear as blurring and ghost repetitions of the moving structures. While the problem with intra-view effects has been effectively addressed using gradient moment nulling techniques, there is no corresponding technique for inter-view effects with equal effectiveness and general applicability. A number of techniques have been proposed for correcting the inter-view effects, and these may be divided into those that minimise the corruption of the data, and those that post-process the data to restore the image. The techniques in the former category are briefly reviewed, then those in the latter category are examined in detail. These are analysed in terms of motion model, model parameter estimation, and data correction.     

Efficacy of motion artifact reduction in neonatal DW segmented EPI at 3 T using phase correction by numerical optimization and segment data swapping

Segmented echoplanar imaging (EPI) is a potentially valuable acquisition method for neonatal diffusion-weighted imaging (DWI) due to the lower acoustic noise levels as well as reduced blurring and distortion associated with it, as compared with single-shot EPI. Reduced acoustic noise may be important for the safety of neonates. However, little information regarding the efficacy of segmented EPI motion correction schemes is available for the neonatal population. We quantitatively assessed the efficacy of a postprocessing technique for motion artifact reduction involving phase correction by nonlinear optimization, alone and in combination with a novel method of utilizing a second data set (referred to as segment data swapping). These methods were applied to three-directional eight-segment echoplanar DW images obtained from 13 sedated neonates and to nine-directional DW images from 3 unsedated neonates. For comparison, the efficacy of the nonlinear optimization method was also evaluated in four adults. Motion correction efficacy was quantified using the motion artifact-to-signal ratio (ASR). The median, 70th percentile and 90th percentile ASR values obtained from neonatal three-directional DWI using nonlinear optimization alone were 2.8%, 4.6% and 9.6%, respectively. Efficacy improved (P<.005), particularly in dealing with the images most difficult to correct, when the phase correction by numerical optimization was combined with segment data swapping (median ASR=1.9%, 70th percentile ASR=2.7%, 90th percentile ASR=4.3%). Similar results were obtained for nine-directional diffusion tensor imaging. Nonlinear optimization alone applied to adult images showed significantly (P<.001) lower ASR values (median ASR=0.9%, 70th percentile ASR=2.1%, 90th percentile ASR=4.1%), demonstrating the greater challenge in DWI of neonates with segmented EPI. In conclusion, phase correction by nonlinear optimization provides effective motion correction for neonatal DW eight-segment EPI, especially when used in conjunction with segment data swapping.     

DC artifact correction for arbitrary phase-cycling sequence

In magnetic resonance imaging (MRI), a non-zero offset in the receiver baseline signal during acquisition results in a bright spot or a line artifact in the center of the image known as a direct current (DC) artifact. Several methods have been suggested in the past for the removal or correction of DC artifacts in MR images, however, these methods cannot be applied directly when a specific phase-cycling technique is used in the imaging sequence. In this work, we proposed a new, simple technique that enables correction of DC artifacts for any arbitrary phase-cycling imaging sequences. The technique is composed of phase unification, DC offset estimation and correction, and phase restoration. The feasibility of the proposed method was demonstrated via phantom and in vivo experiments with a multiple phase-cycling balanced steady-state free precession (bSSFP) imaging sequence. Results showed successful removal of the DC artifacts in images acquired using bSSFP with phase-cycling angles of 0°, 90°, 180°, and 270°, indicating potential feasibility of the proposed method to any imaging sequence with arbitrary phase-cycling angles.     

Accurate and sensitive measurements of magnetic susceptibility using echo planar imaging

Susceptibility differences are common causes for artifacts in magnetic resonance (MR); therefore, it is important to choose phantom materials in a way that these artifacts are kept at a minimum. In this study, a previously proposed MR imaging (MRI) method [Beuf O, Briguet A, Lissac M, Davis R. Magnetic resonance imaging for the determination of magnetic susceptibility of materials. J Magn Reson 1996; Series B(112):111-118] was improved to facilitate sensitive in-house measurements of different phantom materials so that such artifacts can more easily be minimized. Using standard MRI protocols and distilled water as reference, we measured magnetic volume susceptibility differences with a clinical MR system. Two imaging techniques, echo planar imaging (EPI) and spin echo, were compared using liquid samples whose susceptibilities were verified by MR spectroscopy. The EPI sequence has a very narrow bandwidth in the phase-encoding direction, which gives an increased sensitivity to magnetic field inhomogeneities. All MRI measurements were evaluated in two ways: (1) manual image analysis and (2) model fitting. The narrow bandwidth of the EPI made it possible to detect very small susceptibility differences (equivalent susceptibility difference, Deltachi(e)> or =0.02 ppm), and even plastics could be measured. Model fitting yielded high accuracy and high sensitivity and was less sensitive to other image artifacts as compared with manual image analysis.     

An unsupervised deep learning technique for susceptibility artifact correction in reversed phase-encoding EPI images

Echo planar imaging (EPI) is a fast and non-invasive magnetic resonance imaging technique that supports data acquisition at high spatial and temporal resolutions. However, susceptibility artifacts, which cause the misalignment to the underlying structural image, are unavoidable distortions in EPI. Traditional susceptibility artifact correction (SAC) methods estimate the displacement field by optimizing an objective function that involves one or more pairs of reversed phase-encoding (PE) images. The estimated displacement field is then used to unwarp the distorted images and produce the corrected images. Since this conventional approach is time-consuming, we propose an end-to-end deep learning technique, named S-Net, to correct the susceptibility artifacts the reversed-PE image pair. The proposed S-Net consists of two components: (i) a convolutional neural network to map a reversed-PE image pair to the displacement field; and (ii) a spatial transform unit to unwarp the input images and produce the corrected images. The S-Net is trained using a set of reversed-PE image pairs and an unsupervised loss function, without ground-truth data. For a new image pair of reversed-PE images, the displacement field and corrected images are obtained simultaneously by evaluating the trained S-Net directly. Evaluations on three different datasets demonstrate that S-Net can correct the susceptibility artifacts in the reversed-PE images. Compared with two state-of-the-art SAC methods (TOPUP and TISAC), the proposed S-Net runs significantly faster: 20 times faster than TISAC and 369 times faster than TOPUP, while achieving a similar correction accuracy. Consequently, S-Net accelerates the medical image processing pipelines and makes the real-time correction for MRI scanners feasible. Our proposed technique also opens up a new direction in learning-based SAC.     

A comparison study of multishot vs. single-shot DWI-EPI in the neonatal brain: reduced effects of ghosting compared to adults

In the neonatal brain, it is important to use a fast imaging technique to acquire all diffusion weighted images (DWI) for apparent diffusion coefficient (ADC) calculation. Taking into account the occurrence of typical echo planar imaging (EPI) artifacts, we have investigated whether single-shot (SSh) or multishot (MSh) DWI-EPI should be preferred. In 14 neonates, 17 adult patients and 5 adult volunteers, DWIs are obtained both with SSh and MSh EPI. The occurrence of artifacts and their influence on the ADC are explored and further quantified using simulations and phantom studies. Two radiologists scored overall image quality and diagnosability of all images. Single-shot and MSh DWI-EPI scored equally well in neonates with respect to overall image quality and diagnosability. In newborns, more motion artifacts in MSh can be noticed while N/2-ghost artifacts in SSh occur less frequently than in adults. Both N/2-ghost and motion artifacts result in significant ADC abnormalities. There is a serious risk that these artifacts will be mistaken for genuine diffusion abnormalities. N/2-ghost artifacts are hardly noticed in the neonatal brain, which might be due to smaller cerebrospinal fluid (CSF) velocity than in adults. Apparent diffusion coefficient values in MSh are unreliable if motion occurs. We conclude that for ADC calculations in neonates SSh DWI-EPI is more reliable than MSh.     

Prospective motion correction for 3D pseudo-continuous arterial spin labeling using an external optical tracking system

Head motion is an unsolved problem in magnetic resonance imaging (MRI) studies of the brain. Real-time tracking using a camera has recently been proposed as a way to prevent head motion artifacts. As compared to navigator-based approaches that use MRI data to detect and correct motion, optical motion correction works independently of the MRI scanner, thus providing low-latency real-time motion updates without requiring any modifications to the pulse sequence. The purpose of this study was two-fold: 1) to demonstrate that prospective optical motion correction using an optical camera mitigates artifacts from head motion in three-dimensional pseudo-continuous arterial spin labeling (3D PCASL) acquisitions and 2) to assess the effect of latency differences between real-time optical motion tracking and navigator-style approaches (such as PROMO). An optical motion correction system comprising a single camera and a marker attached to the patient's forehead was used to track motion at a rate of 60 fps. In the presence of motion, continuous tracking data from the optical system was used to update the scan plane in real-time during the 3D-PCASL acquisition. Navigator-style correction was simulated by using the tracking data from the optical system and performing updates only once per repetition time. Three normal volunteers and a patient were instructed to perform continuous and discrete head motion throughout the scan. Optical motion correction yielded superior image quality compared to uncorrected images or images using navigator-style correction. The standard deviations of pixel-wise CBF differences between reference and non-corrected, navigator-style-corrected and optical-corrected data were 14.28, 14.35 and 11.09 mL/100 g/min for continuous motion, and 12.42, 12.04 and 9.60 mL/100 g/min for discrete motion. Data obtained from the patient revealed that motion can obscure pathology and that application of optical prospective correction can successfully reveal the underlying pathology in the presence of head motion.     

自导航快速自旋回波在低场MRI上的实现

低场磁共振成像仪一般需采用数据累加的办法来提高图像信噪比,这样会延长扫描时间,因此更易受运动伪影的影响. 为了解决运动伪影问题,本文在低场磁共振成像仪上实现了自导航快速自旋回波去运动伪影成像技术,并且与常规快速自旋回波序列进行了临床对比实验. 结果表明,与常规快速自旋回波序列相比,采用自导航快速自旋回波技术后,由于病人运动导致的伪影得到明显地抑制.      

Motion correction based reconstruction method for compressively sampled cardiac MR imaging

Respiratory motion during Magnetic Resonance (MR) acquisition causes strong blurring artifacts in the reconstructed images. These artifacts become more pronounced when used with the fast imaging reconstruction techniques like compressed sensing (CS). Recently, an MR reconstruction technique has been done with the help of compressed sensing (CS), to provide good quality sparse images from the highly under-sampled k-space data. In order to maximize the benefits of CS, it is obvious to use CS with the motion corrected samples. In this paper, we propose a novel CS based motion corrected image reconstruction technique. First, k-space data have been assigned to different respiratory state with the help of frequency domain phase correlation method. Then, multiple sparsity constraints has been used to provide good quality reconstructed cardiac cine images with the highly under-sampled k-space data. The proposed method exploits the multiple sparsity constraints, in combination with demon based registration technique and a novel reconstruction technique to provide the final motion free images. The proposed method is very simple to implement in clinical settings as compared to existing motion corrected methods. The performance of the proposed method is examined using simulated data and clinical data. Results show that this method performs better than the reconstruction of CS based method of cardiac cine images. Different acceleration rates have been used to show the performance of the proposed method.     

Respiratory motion compensation using data binning in dynamic contrast enhanced golden-angle radial MRI

GRASP (Golden-Angle Radial Sparse Parallel MRI) is a data acquisition and reconstruction technique that combines parallel imaging and golden-angle radial sampling. The continuously acquired free breathing Dynamic Contrast Enhanced (DCE) golden-angle radial MRI data of liver and abdomen has artifacts due to respiratory motion, resulting in low vessel-tissue contrast that makes GRASP reconstructed images less suitable for diagnosis. In this paper, DCE golden-angle radial MRI data of abdomen and liver perfusion is sorted into different motion states using the self-gating property of radial acquisition and then reconstructed using GRASP. Three methods of amplitude-based data binning namely uniform binning, adaptive binning and optimal binning are applied on the DCE golden-angle radial data to extract different motion states and a comparison is performed with the conventional GRASP reconstruction. Also, a comparison among the amplitude-based data binning techniques is performed and benefits of each of these binning techniques are discussed from a clinical perspective. The image quality assessment in terms of hepatic vessel clarity, liver edge sharpness, contrast enhancement clarity and streaking artifacts is performed by a certified radiologist. The results show that DCE golden-angle radial trajectories benefit from all the three types of amplitude-based data binning methods providing improved reconstruction results. The choice of binning technique depends upon the clinical application e.g. uniform and adaptive binning are helpful for a detailed analysis of lesion characteristic and contrast enhancement in different motion states while optimal binning can be used when clinical analysis requires a single image per contrast enhancement phase with no motion blurring artifacts.     

Correction of out-of-FOV motion artifacts using convolutional neural network

PurposeSubject motion during MRI scan can result in severe degradation of image quality. Existing motion correction algorithms rely on the assumption that no information is missing during motions. However, this assumption does not hold when out-of-FOV motion happens. Currently available algorithms are not able to correct for image artifacts introduced by out-of-FOV motion. The purpose of this study is to demonstrate the feasibility of incorporating convolutional neural network (CNN) derived prior image into solving the out-of-FOV motion problem.Methods and materialsA modified U-net network was proposed to correct out-of-FOV motion artifacts by incorporating motion parameters into the loss function. A motion model based data fidelity term was applied in combination with the CNN prediction to further improve the motion correction performance. We trained the CNN on 1113 MPRAGE images with simulated oscillating and sudden motion trajectories, and compared our algorithm to a gradient-based autofocusing (AF) algorithm in both 2D and 3D images. Additional experiment was performed to demonstrate the feasibility of transferring the networks to different dataset. We also evaluated the robustness of this algorithm by adding Gaussian noise to the motion parameters. The motion correction performance was evaluated using mean square error (NMSE), peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM).ResultsThe proposed algorithm outperformed AF-based algorithm for both 2D (NMSE: 0.0066 ± 0.0009 vs 0.0141 ± 0.008, P < .01; PSNR: 29.60 ± 0.74 vs 21.71 ± 0.27, P < .01; SSIM: 0.89 ± 0.014 vs 0.73 ± 0.004, P < .01) and 3D imaging (NMSE: 0.0067 ± 0.0008 vs 0.070 ± 0.021, P < .01; PSNR: 32.40 ± 1.63 vs 22.32 ± 2.378, P < .01; SSIM: 0.89 ± 0.01 vs 0.62 ± 0.03, P < .01). Robust reconstruction was achieved with 20% data missed due to the out-of-FOV motion.ConclusionIn conclusion, the proposed CNN-based motion correction algorithm can significantly reduce out-of-FOV motion artifacts and achieve better image quality compared to AF-based algorithm.     

Zero and first-order phase shift correction for field map estimation with dual-echo GRE using bipolar gradients

A simple phase error correction technique used for field map estimation with a generally available dual-echo gradient-echo (GRE) sequence is presented. Magnetic field inhomogeneity maps estimated using two separate GRE volume acquisitions at different echo times are prone to dynamic motion errors between acquisitions. By using the dual-echo sequence, the data are collected during two back-to-back readout gradients in opposite polarity after a single radio frequency pulse, and interecho motion artifacts and alignment errors in field map estimation can be factored out. Residual phase error from the asymmetric readout pulses is modeled as an affine term in the readout direction. Results from phantom and human data suggest that the first-order phase correction term stays constant over time and, hence, can be applied to different data acquired with the same protocol over time. The zero-order phase correction term may change with time and is estimated empirically for different scans.     

小动物高分辨扩散加权成像在临床 MRI 上的实现

在临床用MRI系统上对小动物扩散加权成像一般采用回波平面成像序列,但是回波平面成像易受偏共振效应的影响,得到的图像伪影大、几何变形严重、图像分辨率低,无法探究微小的生物组织结构. 该文报道了在临床用3 T MRI系统上采用自旋回波序列实现了高分辨扩散加权成像. 为减少运动伪影,序列中整合了导航回波矫正技术. 对脑缺血模型大鼠脑部的扫描结果显示,自旋回波扩散加权序列获得的图像基本没有发生形变,并且具有较高的分辨率和较好的信噪比.     

Influence of the source's energy fluctuation on computational ghost imaging and effective correction approaches

We investigate the influence of the source's energy fluctuation on both computational ghost imaging and computational ghost imaging via sparsity constraint,and if the reconstruction quality will decrease with the increase of the source's energy fluctuation.In order to overcome the problem of image degradation,a correction approach against the source's energy fluctuation is proposed by recording the source's fluctuation with a monitor before modulation and correcting the echo signal or the intensity of computed reference light field with the data recorded by the monitor.Both the numerical simulation and experimental results demonstrate that computational ghost imaging via sparsity constraint can be enhanced by correcting the echo signal or the intensity of computed reference light field,while only correcting the echo signal is valid for computational ghost imaging.     

High resolution diffusion weighted magnetic resonance imaging of the pancreas using reduced field of view single-shot echo-planar imaging at 3 T

Diffusion weighted magnetic resonance imaging (DWI) has been mostly acquired using single-shot echo-planar imaging (ss EPI) to minimize motion induced artifacts. The spatial resolution, however, is inherently limited in ss EPI especially for abdominal imaging, even with the advances in parallel imaging. A novel method of reduced Field of View ss EPI (rFOV ss EPI) has achieved high resolution DWI in human carotid artery, spinal cord with reduced blurring and higher spatial resolution than conventional ss EPI, but it has not been used to pancreas imaging. In the work, comparisons between the full FOV ss-DW EPI and rFOV ss-DW EPI in image qualities and ADC values of pancreatic tumors and normal pancreatic tissues were performed to demonstrate the feasibility of pancreatic high resolution rFOV DWI. There were no significant differences in the mean ADC values between full FOV DWI and rFOV DWI for the 17 subjects using b = 600 s/mm² (P = 0.962). However, subjective scores of image quality was significantly higher at rFOV ss DWI (P = 0.008 and 0.000 for b-value = 0 s/mm² and 600 s/mm² respectively). The spatial resolution of DWI for pancreas was increased by a factor of over 2.0 (from almost 3.0 mm/pixel to 1.25 mm/pixel) using rFOV ss EPI technique. Reduced FOV ss EPI can provide good DW images and is promising to benefit applications for pancreatic diseases.     

Anisotropic field-of-view shapes for improved PROPELLER imaging

The Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction (PROPELLER) method for magnetic resonance imaging data acquisition and reconstruction has the highly desirable property of being able to correct for motion during the scan, making it especially useful for imaging pediatric or uncooperative patients and diffusion imaging. This method nominally supports a circular field of view (FOV), but tailoring the FOV for noncircular shapes results in more efficient, shorter scans. This article presents new algorithms for tailoring PROPELLER acquisitions to the desired FOV shape and size that are flexible and precise. The FOV design also allows for rotational motion which provides better motion correction and reduced aliasing artifacts. Some possible FOV shapes demonstrated are ellipses, ovals and rectangles, and any convex, pi-symmetric shape can be designed. Standard PROPELLER reconstruction is used with minor modifications, and results with simulated motion presented confirm the effectiveness of the motion correction with these modified FOV shapes. These new acquisition design algorithms are simple and fast enough to be computed for each individual scan. Also presented are algorithms for further scan time reductions in PROPELLER echo-planar imaging (EPI) acquisitions by varying the sample spacing in two directions within each blade.