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.     

A constrained Gauss-Seidel method for correction of point spread function effect in MR spectroscopic imaging

Magnetic resonance spectroscopic imaging is limited by a low signal-to-noise ratio, so a compromise between spatial resolution and examination time is needed in clinical application. The reconstruction of truncated signal introduces a Point Spread Function that considerably affects the spatial resolution. In order to reduce spatial contamination, three methods, applied after Fourier transform image reconstruction, based on deconvolution or iterative techniques are tested to decrease Point Spread Function contamination. A Gauss-Seidel (GS) algorithm is used for iterative techniques with and without a non-negative constraint (GS+). Convergence and noise dependence studies of the GS algorithm have been done. The linear property of contamination was validated on a point sample phantom. A significant decrease of contamination without broadening the spatial resolution was obtained with GS+ method compared to a conventional apodization. This post-processing method can provide a contrast enhancement of clinical spectroscopic images without changes in acquisition time.     

Coordinate difference homogenization matching method for motion correction in 3D range-intensity correlation laser imaging

This Letter proposes a coordinate difference homogenization matching method to solve motion influence in three-dimensional(3D) range-intensity correlation laser imaging. Firstly, features and feature pairs of gate images are obtained by speeded-up robust figures and bi-directional feature matching methods. The original mean value of the feature-pair coordinate differences is calculated. Comparing the coordinate differences with the original mean value, the wrong feature pairs are removed, and then an optimized mean value is updated. The final feature-pair coordinates are re-registered based on the updated mean value. Thus, an accurate transformation is established to rectify motion gate images for 3D reconstruction. In the experiment, a 3D image of a tower at 780 m is successfully captured by our laser gated imaging system on a pan–tilt device.     

Concurrent correction of geometric distortion and motion using the map-slice-to-volume method in echo-planar imaging

The accuracy of measuring voxel intensity changes between stimulus and rest images in fMRI echo-planar imaging (EPI) data is severely degraded in the presence of head motion. In addition, EPI is sensitive to susceptibility-induced geometric distortions. Head motion causes image shifts and associated field map changes that induce different geometric distortion at different time points. Conventionally, geometric distortion is "corrected" with a static field map independently of image registration. That approach ignores all field map changes induced by head motion. This work evaluates the improved motion correction capability of mapping slice to volume with concurrent iterative field corrected reconstruction using updated field maps derived from an initial static field map that has been spatially transformed and resampled. It accounts for motion-induced field map changes for translational and in-plane rotation motion. The results from simulated EPI time series data, in which motion, image intensity and activation ground truths are available, show improved accuracy in image registration, field corrected image reconstruction and activation detection.     

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.     

Quantitative assessment of motion correction for high angular resolution diffusion imaging

Several methods have been proposed for motion correction of high angular resolution diffusion imaging (HARDI) data. There have been few comparisons of these methods, partly due to a lack of quantitative metrics of performance. We compare two motion correction strategies using two figures of merit: displacement introduced by the motion correction and the 95% confidence interval of the cone of uncertainty of voxels with prolate tensors. What follows is a general approach for assessing motion correction of HARDI data that may have broad application for quality assurance and optimization of postprocessing protocols. Our analysis demonstrates two important issues related to motion correction of HARDI data: (1) although neither method we tested was dramatically superior in performance, both were dramatically better than performing no motion correction, and (2) iteration of motion correction can improve the final results. Based on the results demonstrated here, iterative motion correction is strongly recommended for HARDI acquisitions.     

MR imaging of cervical spine motion with HASTE

The HASTE (half-Fourier acquisition single-shot turbo spin-echo) technique delivers images with T2-weighting in about half a second and could be ideal for fast dynamic studies when T2-weighting is needed. We evaluated cardiac-triggered HASTE to study cervical spine flexion/extension. The cervical spines of ten asymptomatic volunteers were studied during flexion/extension motion on a 1.5 Tesla imager using a cardiac triggered version of the HASTE technique. Midline sagittal images were acquired every 2 to 3 s during neck flexion and extension. Image quality was compared to traditional T2-weighted Turbo spin-echo. The study duration per flexion/ extension was typically less than 20 seconds and well tolerated. The cardiac-gated T2-weighted HASTE images compared favorably to the traditional T2-weighted TSE images in quality and overall anatomic detail. Range of motion averaged: flexion 30 degrees (range 8 degrees -48 degrees) and extension 23 degrees (range 0 degrees -57 degrees ). Greatest motion occurred in the lower cervical spine (C4-C7). At the intervertebral discs the canal diameter, anterior and posterior CSF spaces were widest in neutral position and decreased with flexion and extension. Therefore, Cardiac-gated T2 HASTE sequences provide diagnostic and time-efficient dynamic MR images of cervical spine motion.     

基于CUDA的傅里叶变换成像光谱仪数据重建

为了达到傅里叶变换成像光谱仪(FTIS)数据快速重建的目的,使用GPU并行计算技术设计了基于CUDA(compute unified device architecture)的成像光谱仪快速数据重建优化算法。采用CUDA下的CUFFT库和CUDA并行计算内核,以达到加快成像光谱仪快速数据重建。结果表明,基于CUDA的并行计算技术能有效调动GPU的硬件资源,可大幅度提高光谱重建处理任务的计算效率。如果将该技术应用到更多核的并行计算工作站上,那么单台计算机完成干涉成像光谱仪数据的实时处理任务将成为可能。     

Highly accelerated aortic 4D flow MR imaging with variable-density random undersampling

Purpose

To investigate an effective time-resolved variable-density random undersampling scheme combined with an efficient parallel image reconstruction method for highly accelerated aortic 4D flow MR imaging with high reconstruction accuracy.

Materials and Methods

Variable-density Poisson-disk sampling (vPDS) was applied in both the phase-slice encoding plane and the temporal domain to accelerate the time-resolved 3D Cartesian acquisition of flow imaging. In order to generate an improved initial solution for the iterative self-consistent parallel imaging method (SPIRiT), a sample-selective view sharing reconstruction for time-resolved random undersampling (STIRRUP) was introduced. The performance of different undersampling and image reconstruction schemes were evaluated by retrospectively applying those to fully sampled data sets obtained from three healthy subjects and a flow phantom.

Results

Undersampling pattern based on the combination of time-resolved vPDS, the temporal sharing scheme STIRRUP, and parallel imaging SPIRiT, were able to achieve 6-fold accelerated 4D flow MRI with high accuracy using a small number of coils (N = 5). The normalized root mean square error between aorta flow waveforms obtained with the acceleration method and the fully sampled data in three healthy subjects was 0.04 ± 0.02, and the difference in peak-systolic mean velocity was − 0.29 ± 2.56 cm/s.

Conclusion

Qualitative and quantitative evaluation of our preliminary results demonstrate that time-resolved variable-density random sampling is efficient for highly accelerating 4D flow imaging while maintaining image reconstruction accuracy.     

Evaluation of motion effects on parallel MR imaging with precalibration

Several parallel imaging techniques such as SMASH, SENSE, k-space inherited parallel acquisition (KIPA) and others use reference (calibration) scans to find the parameters required for image reconstruction. Reference data is used to estimate coil sensitivity profiles for image domain techniques such as SENSE or reconstruction coefficients for k-space domain methods such as SMASH and KIPA. Any motion between the reference and accelerated imaging scans can make the reconstruction coefficients determined from the reference scan data suboptimal, resulting in an artifactual reconstruction. This work aims at comparing the effects of motion on the performance of three parallel imaging methods: SENSE, variable-density SENSE and KIPA, which all require one or more reference scans for calibration.     

基于场景的三通道偏振成像系统的校正方法

基于定标的三通道偏振成像系统的校正方法在对通道响应度非一致性的标定过程中操作繁琐,无法根据实际环境的变化随时校正,影响了三通道偏振成像系统的实用性。为了解决这一问题,提出了一种基于场景的三通道成像系统的校正方法。该方法基于对场景中偏振信息的统计,分离出复杂场景中无偏振性的场景分量,简单快速地修正了各通道的灰度响应差异。实验结果表明：该方法克服了通道响应度非一致性的影响,突出不同材质物体的偏振差异,使三通道偏振成像系统的成像效果接近单通道偏振成像系统水平,极大地提高了系统的实用性。     

基于场景的三通道偏振成像系统的校正方法

基于定标的三通道偏振成像系统的校正方法在对通道响应度非一致性的标定过程中操作繁琐,无法根据实际环境的变化随时校正,影响了三通道偏振成像系统的实用性。为了解决这一问题,提出了一种基于场景的三通道成像系统的校正方法。该方法基于对场景中偏振信息的统计,分离出复杂场景中无偏振性的场景分量,简单快速地修正了各通道的灰度响应差异。实验结果表明:该方法克服了通道响应度非一致性的影响,突出不同材质物体的偏振差异,使三通道偏振成像系统的成像效果接近单通道偏振成像系统水平,极大地提高了系统的实用性。     

Elimination of motion and pulsation artifacts using BLADE sequences in knee MR imaging

The purpose of this study is to evaluate the ability of proton density (PD)-BLADE sequences in reducing or even eliminating motion and pulsatile flow artifacts in knee magnetic resonance imaging examinations. Eighty consecutive patients, who had been routinely scanned for knee examination, participated in the study. The following pairs of sequences with and without BLADE were compared: (a) PD turbo spin echo (TSE) sagittal (SAG) fat saturation (FS) in 35 patients, (b) PD TSE coronal (COR) FS in 19 patients, (c) T2 TSE axial in 13 patients and (d) PD TSE SAG in 13 patients. Both qualitative and quantitative analyses were performed based on the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and relative contrast (ReCon) measures of normal anatomic structures. The qualitative analysis was performed by experienced radiologists. Also, the presence of image motion and pulsation artifacts was evaluated. Based on the results of the SNR, CRN and ReCon for the different sequences and anatomical structures, the BLADE sequences were significantly superior in 19 cases, whereas the corresponding conventional sequences were significantly superior in only 6 cases. BLADE sequences eliminated motion artifacts in all the cases. However, motion artifacts were shown in (a) six PD TSE SAG FS, (b) three PD TSE COR FS, (c) three PD TSE SAG and (d) two T2 TSE axial conventional sequences. In our results, it was found that, in PD FS sequences (sagittal and coronal), the differences between the BLADE and conventional sequences regarding the elimination of motion and pulsatile flow artifacts were statistically significant. In all the comparisons, the PD FS BLADE sequences (coronal and sagittal) were significantly superior to the corresponding conventional sequences regarding the classification of their image quality. In conclusion, this technique appears to be capable to potentially eliminate motion and pulsatile flow artifacts in MR images.     

Simulation of the influence of magnetic field inhomogeneity and distortion correction in MR imaging

We describe a technique for simulation and correction of the effects of an arbitrary distribution of undesired components of the static and gradient magnetic fields. This technique is applicable to direct Fourier NMR imaging. The mathematical basis and details of this technique are fully described. Computer simulation demonstrates the effectiveness of this method.     

旋转运动声源的频率波动修正波束形成方法

针对前飞状态的旋翼气动噪声信号频率存在周期性波动,且频域波束形成方法只能应用于稳态声源的问题,提出一种频率波动声源的波束形成方法。该方法利用已知的声源频率变化规律进行频率修正,在时域将频率波动信号等效为单频信号,基于该单频信号进行波束形成声源定位,实现了旋转运动的频率波动声源准确定位。数值仿真结果表明,提出的方法能够在频率波动幅值为127 Hz的情况下准确呈现出声源分布情况。在旋翼模型的风洞试验中,利用提出的频域波束形成方法其声成像结果中声源最大能量位置均在旋转轨迹上,而未进行频率修正的波束形成方法结果无法准确呈现出声源的位置。该方法扩展了频域波束形成方法中的单频声源假设,实现了旋转运动声源在频率波动状态下的波束形成,适用于前飞状态下旋翼气动噪声源的声源定位。     

Separable convolution template (SCT) background prediction accelerated by CUDA for infrared small target detection

This paper presents a novel background prediction method for infrared small target detection (ISTD). Using a separable convolution template (SCT) to accelerate the traditional background prediction by graphic processing unit (GPU), the new method provides a significant improvement in the prediction speed, which enables the prediction process in real time. And experimental results show its high efficiency and practical application over previous work. The mathematical approach proposed here could be extended to accelerate the applications referred to image convolutions not only to the infrared field.     

A multi-scale residual network for accelerated radial MR parameter mapping

A deep learning MR parameter mapping framework which combines accelerated radial data acquisition with a multi-scale residual network (MS-ResNet) for image reconstruction is proposed. The proposed supervised learning strategy uses input image patches from multi-contrast images with radial undersampling artifacts and target image patches from artifact-free multi-contrast images. Subspace filtering is used during pre-processing to denoise input patches. For each anatomy and relaxation parameter, an individual network is trained. in vivo T₁ mapping results are obtained on brain and abdomen datasets and in vivo T₂ mapping results are obtained on brain and knee datasets. Quantitative results for the T₂ mapping of the knee show that MS-ResNet trained using either fully sampled or undersampled data outperforms conventional model-based compressed sensing methods. This is significant because obtaining fully sampled training data is not possible in many applications. in vivo brain and abdomen results for T₁ mapping and in vivo brain results for T₂ mapping demonstrate that MS-ResNet yields contrast-weighted images and parameter maps that are comparable to those achieved by model-based iterative methods while offering two orders of magnitude reduction in reconstruction times. The proposed approach enables recovery of high-quality contrast-weighted images and parameter maps from highly accelerated radial data acquisitions. The rapid image reconstructions enabled by the proposed approach makes it a good candidate for routine clinical use.