基于AR模型的最大熵磁共振成像重建算法

本文提出了一种基于ＡＲ模型的磁共振成像算法，通过所获得的自回归系数及线性预测误差，替代了传统的快速傅里叶（ＦＦＴ）重建方法，获得了满意的重建图像，由于在实际系统中，只能得到有限的频谱数据，利用传统的ＦＦＴ方法重建磁共振图像，将导致截断伪影和低的分辨率。本算法利用ＡＲ模型外推未知频谱数据，替代ＦＦＴ方法的填零法重建，并利用ＢＵＲＧ算法中的ＡＲ模型参数计算的有效性，不仅消除了截断伪影，抑制噪声提高了分     

Algebraic reconstruction for magnetic resonance imaging underB0 inhomogeneity

In magnetic resonance imaging, spatial localization is usually achieved using Fourier encoding which is realized by applying a magnetic field gradient along the dimension of interest to create a linear correspondence between the resonance frequency and spatial location following the Larmor equation. In the presence of B₀ inhomogeneities along this dimension, the linear mapping does not hold and spatial distortions arise in the acquired images. In this paper, the problem of image reconstruction under an inhomogeneous field is formulated as an inverse problem of a linear Fredholm equation of the first kind. The operators in these problems are estimated using field mapping and the k-space trajectory of the imaging sequence. Since such inverse problems are known to be ill-posed in general, robust solvers, singular value decomposition and conjugate gradient method, are employed to obtain corrected images that are optimal in the Frobenius norm sense. Based on this formulation, the choice of the imaging sequence for well-conditioned matrix operators is discussed, and it is shown that nonlinear k-space trajectories provide better results. The reconstruction technique is applied to sequences where the distortion is more severe along one of the image dimensions and the two-dimensional reconstruction problem becomes equivalent to a set of independent one-dimensional problems. Experimental results demonstrate the performance and stability of the algebraic reconstruction methods     

Improved reconstruction for MR spectroscopic imaging

Sensitivity limitations of in vivo magnetic resonance spectroscopic imaging (MRSI) require that the extent of spatial-frequency (k-space) sampling be limited, thereby reducing spatial resolution and increasing the effects of Gibbs ringing that is associated with the use of Fourier transform reconstruction. Additional problems occur in the spectral dimension, where quantitation of individual spectral components is made more difficult by the typically low signal-to-noise ratios, variable lineshapes, and baseline distortions, particularly in areas of significant magnetic field inhomogeneity. Given the potential of in vivo MRSI measurements for a number of clinical and biomedical research applications, there is considerable interest in improving the quality of the metabolite image reconstructions. In this report, a reconstruction method is described that makes use of parametric modeling and MRI-derived tissue distribution functions to enhance the MRSI spatial reconstruction. Additional preprocessing steps are also proposed to avoid difficulties associated with image regions containing spectra of inadequate quality, which are commonly present in the in vivo MRSI data     

Surface passivation of cadmium zinc telluride radiation detectors by potassium hydroxide solution

The spectral resolution of cadmium zinc telluride (CZT) room temperature nuclear radiation detectors is often limited by the presence of conducting surface species that increase the surface leakage current. Surface passivation plays an important role in reducing this surface leakage current and thereby decreasing the noise of the detectors and improving the spectral energy resolution. Chemical etching with a Br-MeOH solution leaves CZT surfaces rich in Te and is considered as one of the primary causes of the increased surface leakage current. Previous studies have shown that hydrogen peroxide (H₂O₂) forms oxides of tellurium on the CZT surface and thus acts as a good passivating agent. In this study we will present results on the use of potassium hydroxide (KOH) as an alternative passivating agent. The KOH aqueous solution leaves a more stoichiometric (evaluated from the trends in the surface Cd:Te ratio) and smoother CZT surface. The passivation effects of KOH solution on the surface of the CZT have been characterized by current-voltage measurements for different KOH concentrations and etching times for both parallel strip electrodes as well as a metal-semiconductor-metal configuration. The surface chemical composition and its morphology were studied by scanning x-ray photoelectron spectroscopy and atomic force microscopy. The comparison and demonstration of improvements in the spectral resolution of the CZT detectors (based on ²⁴¹Am spectra) with and without the KOH treatment are presented.     

Multishot rosette trajectories for spectrally selective MR imaging

In nuclear magnetic resonance, different spectral components often correspond to different chemical species and as such, spectral selectivity can be a valuable tool for diagnostic imaging. In the work presented here, a multishot image acquisition method based upon rosette k-space trajectories has been developed and implemented for spectrally selective magnetic resonance imaging (MRI). Parametric forms for the gradient waveforms and design constraints are derived, and an example multishot gradient design is presented. The spectral behaviour for this imaging method is analyzed in a simulation model. For frequencies that are near to the resonant frequency, this method results in a lower intensity, but undistorted image, while for frequencies that are off-resonance by a large amount, the object is incoherently dephased into noise. A method by which acquisitions are delayed by small amounts is introduced to further reduce the residual intensity for off-resonant signals. An image reconstruction method based on convolution gridding, including a correction method for small amounts of magnetic field inhomogeneity, is implemented. Finally, the spectral selectivity is demonstrated in vivo in a study in which both water and lipid images are generated from a single imaging data set     

Image reconstruction in magnetic resonance conductivity tensor imaging (MRCTI)

Almost all magnetic resonance electrical impedance tomography (MREIT) reconstruction algorithms proposed to date assume isotropic conductivity in order to simplify the image reconstruction. However, it is well known that most of biological tissues have anisotropic conductivity values. In this study, four novel anisotropic conductivity reconstruction algorithms are proposed to reconstruct high resolution conductivity tensor images. Performances of these four algorithms and a previously proposed algorithm are evaluated in several aspects and compared.     

Magnetic resonance electrical impedance tomography (MREIT): simulation study of J-substitution algorithm

We developed a new image reconstruction algorithm for magnetic resonance electrical impedance tomography (MREIT). MREIT is a new EIT imaging technique integrated into magnetic resonance imaging (MRI) system. Based on the assumption that internal current density distribution is obtained using magnetic resonance imaging (MRI) technique, the new image reconstruction algorithm called J-substitution algorithm produces cross-sectional static images of resistivity (or conductivity) distributions. Computer simulations show that the spatial resolution of resistivity image is comparable to that of MRI. MREIT provides accurate high-resolution cross-sectional resistivity images making resistivity values of various human tissues available for many biomedical applications.     

Fast,iterative image reconstruction for MRI in the presence of field inhomogeneities

In magnetic resonance imaging, magnetic field inhomogeneities cause distortions in images that are reconstructed by conventional fast Fourier trasform (FFT) methods. Several noniterative image reconstruction methods are used currently to compensate for field inhomogeneities, but these methods assume that the field map that characterizes the off-resonance frequencies is spatially smooth. Recently, iterative methods have been proposed that can circumvent this assumption and provide improved compensation for off-resonance effects. However, straightforward implementations of such iterative methods suffer from inconveniently long computation times. This paper describes a tool for accelerating iterative reconstruction of field-corrected MR images: a novel time-segmented approximation to the MR signal equation. We use a min-max formulation to derive the temporal interpolator. Speedups of around 60 were achieved by combining this temporal interpolator with a nonuniform fast Fourier transform with normalized root mean squared approximation errors of 0.07%. The proposed method provides fast, accurate, field-corrected image reconstruction even when the field map is not smooth.     

Noninvasive imaging of bioimpedance distribution by means of current reconstruction magnetic resonance electrical impedance tomography

We have developed a novel magnetic resonance electrical impedance tomography (MREIT) algorithm-current reconstruction MREIT algorithm-for noninvasive imaging of electrical impedance distribution of a biological system using only one component of magnetic flux density. The newly proposed algorithm uses the inverse of Biot-Savart Law to reconstruct the current density distribution, and then, uses a modified J-substitution algorithm to reconstruct the conductivity image. A series of computer simulations has been conducted to evaluate the performance of the proposed current reconstruction MREIT algorithm with simulation settings for breast cancer imaging applications, with consideration of measurement noise, current injection strength, size of simulated tumors, spatial resolution, and position dependency. The present simulation results are highly promising, demonstrating the high spatial resolution, high accuracy in conductivity reconstruction, and robustness against noise of the proposed algorithm for imaging electrical impedance of a biological system. The present MREIT method may have potential applications to breast cancer imaging and imaging of other organs.     

Fast magnetic resonance imaging with simultaneously oscillating and rotating fiell gradients

We present an approach to magnetic resonance imaging employing a magnetic field gradient that rotates 180 degrees in the image plane while the gradient magnitude oscillates rapidly during the rotation. A single free induction decay recorded during this rotation contains all the information needed to reconstruct a two-dimensional image. In effect, each sinusoidal oscillation of the gradient provides information corresponding to one projection in more conventional Fourier-projection approaches. Since the data acquisition can be achieved in a period less than T2, the method offers the potential of great speed, which is limited only by the gradient modulation frequency. An explicit image reconstruction formula is derived that gives, when evaluated, a reconstruction of the magnetization equal to the true magnetization convolved with a space-invariant point spread function. This point spread function is derived and characterizes the resolving power and sidelobe response of the technique. Moreover, we derive a similar reconstruction formula which is valid when known inhomogeneities in the static field H0 and T2 are present. Finally, we show how the general approach can be extended to three dimensions.     

Conjugate phase MRI reconstruction with spatially variant sample density correction

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.     

Error analysis of nonconstant admittivity for MR-based electric property imaging

Magnetic resonance electrical property tomography (MREPT) is a new imaging modality to visualize a distribution of admittivity γ = σ+iωε inside the human body where σ and ε denote electrical conductivity and permittivity, respectively. Using B1 maps acquired by an magnetic resonance imaging scanner, it produces cross-sectional images of σ and ε at the Larmor frequency. Since current MREPT methods rely on an assumption of a locally homogeneous admittivity, there occurs a reconstruction error where this assumption fails. Rigorously analyzing the reconstruction error in MREPT, we showed that the error is fundamental and may cause technical difficulties in interpreting MREPT images of a general inhomogeneous object. We performed numerical simulations and phantom experiments to quantitatively support the error analysis. We compared the MREPT image reconstruction problem with that of magnetic resonance electrical impedance tomography (MREIT) to highlight distinct features of both methods to probe the same object in terms of its high- and low-frequency conductivity distributions, respectively. MREPT images showed large errors along boundaries where admittivity values changed whereas MREIT images showed no such boundary effects. Noting that MREIT makes use of the term neglected in MREPT, a novel MREPT admittivity image reconstruction method is proposed to deal with the boundary effects, which requires further investigation on the complex directional derivative in the real Euclidian space [Formula: see text].     

基于小波域的压缩感知超分辨率重建方法

为了提高超分辨率图像的重构效果,提出了一种基于小波域的压缩感知超分辨率重建方法.首先采用小波变换对低分辨率图像进行分解,得到低分辨率图像的低频子带与高频子带,然后采用压缩感知技术分别对低频子带和高频子带进行重建,并通过小波逆变换得到最终重建图像,最后在MATLAB 2012平台上进行仿真实验.结果表明,相对于其他图像重建方法,本文方法的重建图像视觉效果更加理想,不仅提高了低分辨率图像重建精度,而且提高了图像重建效率,可以满足图像处理的实时性、在线性要求.     

Towards cardiac C-arm computed tomography

Cardiac interventional procedures would benefit tremendously from sophisticated three-dimensional image guidance. Such procedures are typically performed with C-arm angiography systems, and tomographic imaging is currently available only by using preprocedural computed tomography (CT) or magnetic resonance imaging (MRI) scans. Recent developments in C-arm CT (Angiographic CT) allow three-dimensional (3-D) imaging of low contrast details with angiography imaging systems for noncardiac applications. We propose a new approach for cardiac imaging that takes advantage of this improved contrast resolution and is based on intravenous contrast injection. The method is an analogue to multisegment reconstruction in cardiac CT adapted to the much slower rotational speed of C-arm CT. Motion of the heart is considered in the reconstruction process by retrospective electrocardiogram (ECG)-gating, using only projections acquired at a similar heart phase. A series of N almost identical rotational acquisitions is performed at different heart phases to obtain a complete data set at a minimum temporal resolution of 1/N of the heart cycle time. First results in simulation, using an experimental phantom, and in preclinical in vivo studies showed that excellent image quality can be achieved.     

A Super-Resolution Framework for 3-D High-Resolution and High-Contrast Imaging Using 2-D Multislice MRI

A novel super-resolution reconstruction (SRR) framework in magnetic resonance imaging (MRI) is proposed. Its purpose is to produce images of both high resolution and high contrast desirable for image-guided minimally invasive brain surgery. The input data are multiple 2-D multislice inversion recovery MRI scans acquired at orientations with regular angular spacing rotated around a common frequency encoding axis. The output is a 3-D volume of isotropic high resolution. The inversion process resembles a localized projection reconstruction problem. Iterative algorithms for reconstruction are based on the projection onto convex sets (POCS) formalism. Results demonstrate resolution enhancement in simulated phantom studies, and ex vivo and in vivo human brain scans, carried out on clinical scanners. A comparison with previously published SRR methods shows favorable characteristics in the proposed approach.     

CZT面元像素探测器的研制及其幅度修正技术的实现

根据CdZnTe（CZT）面元像素探测器基本原理,测试分析了像素阵列CZT晶体漏电流特性。建立了基于数字脉冲处理方式的11 mm×11 mm×3 mm尺寸4×4像素阵列CZT探测系统。采用137Cs 662 keV伽玛源测试得到探测系统响应脉冲幅度谱,平均能量分辨率为3.3%,全能谱峰（FWHM）为21.85 keV。...     

Constrained reconstruction applied to 2-D chemical shift imaging

The method of constrained reconstruction, previously applied to magnetic resonance imaging (MRI), is extended to magnetic resonance spectroscopy. This method assumes a model for the MR signal. The model parameters are estimated directly from the phase encoded data. This process obviates the need for the fast Fourier transform (FFT) (which often exhibits limited resolution and ringing artifact). The technique is tested on simulated data, phantom data, and data acquired from human liver in vivo. In each case, constrained reconstruction offers spatial resolution superior to that obtained with the FFT     

生成式对抗神经网络的多帧红外图像超分辨率重建

生成式对抗神经网络在约束图像生成表现出了巨大潜力,使得其适合运用于图像超分辨率重建。但是使用生成式对抗神经网络重建后的超分辨率图像存在过度平滑,缺少高频细节信息的缺点。针对单帧图像超分辨率重建方法不能有效利用图像序列间的时间-空间相关性的问题,提出了一种基于生成式对抗神经网络的多帧红外图像超分辨率重建方法（M-GANs）。首先,对低分辨率图像序列进行运动补偿;其次,使用权值表示卷积层对运动补偿后的图像序列进行权值转换计算;最后,将其输入生成式对抗重建网络,输出重建后的高分辨率图像。实验结果表明:文中方法在主观及客观评价中均优于当前代表性的超分辨率重建方法。     

On‐Chip Super‐Resolution Imaging with Fluorescent Polymer Films

Wide field‐of‐view (FOV), label‐free, super‐resolution imaging is demonstrated using a specially designed waveguide chip that can illuminate a sample with multicolor evanescent waves travelling along different directions. The method is enabled by a polymer fluorescent film that emits over a broad wavelength range. Its polygonal geometry ensures coverage over all illumination directions, enabling high‐fidelity image reconstruction while minimizing distortion and image blurring. By frequency shifting and iterative stitching of different spatial frequencies in Fourier space, the reconstruction of 2D samples is achieved without distortion over wide FOVs. The fabrication process is facile and compatible with conventional semiconductor‐fabrication methods. The super‐resolution chip (SRC) can thus be produced with high yield, offering opportunities for potential conjunction of super‐resolution techniques integrated optical circuits or for the development of single‐use diagnostic kits.     

Signal compensation and compressed sensing for magnetization-prepared MR angiography

Magnetization-prepared acquisitions offer a trade-off between image contrast and scan efficiency for magnetic resonance imaging. Because the prepared signals gradually decay, the contrast can be improved by frequently repeating the preparation, which in turn significantly increases the scan time. A common solution is to perform the data collection progressing from low- to high-spatial-frequency samples following each preparation. Unfortunately, this leads to loss of spatial resolution, and thereby image blurring. In this work, a new technique is proposed that first corrects the signal decay in high-frequency data to mitigate the resolution loss and improve the image contrast without reducing the scan efficiency. The proposed technique then employs a sparsity-based nonlinear reconstruction to further improve the image quality. In addition to reducing the amplified high-frequency noise, this reconstruction extrapolates missing k-space samples in the case of undersampled compressed-sensing acquisitions. The technique is successfully demonstrated for noncontrast-enhanced flow-independent angiography of the lower extremities, an application that substantially benefits from both the signal compensation and the nonlinear reconstruction.