Reducing inhomogeneity artifacts in functional MRI of human brain activation-thin sections vs gradient compensation

We evaluated two methods for correcting inhomogeneity-induced signal losses in magnetic resonance gradient-echo imaging that either use gradient compensation or simply acquire thin sections. The strategies were tested in the human brain in terms of achievable quality of T2*-weighted images at the level of the hippocampus and of functional activation maps of the visual cortex. Experiments were performed at 2.0 T and based on single-shot echo-planar imaging at 2. 0 x 2.0 mm(2) resolution, 4 mm section thickness, and 2.0 s temporal resolution. Gradient compensation involved a sequential 16-step variation of the refocusing lobe of the slice-selection gradient (TR/TE = 125/53 ms, flip angle 15 degrees ), whereas thin sections divided the 4-mm target plane into either four 1-mm or eight 0.5-mm interleaved multislice acquisitions (TR/TE = 2000/54 ms, flip angle 70 degrees ). Both approaches were capable of alleviating the inhomogeneity problem for structures in the base of the brain. When compared to standard 4-mm EPI, functional mapping in the visual cortex was partially compromised because of a lower signal-to-noise ratio of inhomogeneity-corrected images by either method. Relative to each other, consistently better results were obtained with the use of contiguous thin sections, in particular for a thickness of 1 mm. Multislice acquisitions of thin sections require minimal technical adjustments.     

Three-dimensional numerical simulations of susceptibility-induced magnetic field inhomogeneities in the human head

Three-dimensional numerical simulations of the static magnetic field in the human head were carried out to assess the field inhomogeneity due to magnetic susceptibility differences at tissue interfaces. We used a finite difference method and magnetic permeability distributions obtained by segmentation of computed tomography images. Computations were carried out for four models, consisting of the head and the neck; the head, neck, and shoulders; the head, neck, and thorax; and the head tilted backwards, including the neck and the shoulders. Considerable magnetic field inhomogeneities were observed in the inferior frontal lobes and inferior temporal lobes, particularly near the sphenoid sinus and the temporal bones. Air/tissue interfaces at the shoulders were found to induce substantial magnetic field inhomogeneities in the occipital lobes and the cerebellum, whereas air/tissue interfaces in the lungs appeared to have less influence on the magnetic field in the brain. Tilting the head backwards could significantly reduce the field inhomogeneities superior to the planum sphenoidale as well as in the occipital lobes and the cerebellum.     

The statistical sinogram smoothing via adaptive-weighted total variation regularization for low-dose X-ray CT

Though clinically desired, low-dose X-ray computed tomography (CT) images tend to be degraded by the noise-contaminated sinogram data. Preprocessing the noisy sinogram before filtered back-projection (FBP) is an effective way to solve this problem. This paper presents a statistical sinogram smoothing approach for low-dose CT reconstruction. The approach is obtained by minimizing an energy function consisting of an adaptive-weighted total variation (AWTV) regularization term and a data fidelity term based on the Markov random fields (MRF) framework. The AWTV regularization term can make our algorithm automatically adjust the smoothing degree according to the feature and the level of noise of the smoothed pixel. The experimental results indicate that the proposed approach has the excellent performance in visual effects and quantitative analysis.     

利用偏微分方程的Tetrolet变换图像去噪

对图像进行Tetrolet变换后利用偏微分方程对图像进行了质量改善,仿真结果表明,该算法不仅能有效去除噪声,而且可得到更高的峰值信噪比和更好的视觉效果,去噪后图像较光滑,减少了方块效应,更多地保留了图像边缘和细节等局部特征.     

一种用于CMOS图像传感器的彩色插值算法

讨论一种对CMOS图像传感器输出原始图像的彩色插值的新算法.该算法利用Bayer彩色滤光阵列的色信号特性和自然景物的一些特征,减少了常规插值算法带进的噪声.实验结果表明该算法恢复的图片与常规算法相比,轮廓更清晰,伪色彩更少.     

视频压缩损伤分析及客观测量方法

基于分块DCT的视频压缩方法在数字视频系统中得到了广泛的应用.该方法能有效降低数据量,但同时也带来了压缩损伤.本文从理论上分析了压缩损伤产生的原因,并提出了可对三种主要压缩损伤（振铃现象、块效应和边缘模糊）进行定量测量的方法.实验结果证明,该方法具有可靠、实用的特点.     

基于指数律分布的图像快速盲复原算法

针对现有图像盲复原迭代算法多存在耗时较长和难以保证收敛性等问题,提出一种改进的快速算法.首先根据指数律重建原始图像的频谱,然后利用原始图像和降质图像的频谱关系,采用多方向综合估计方法得到点扩散函数.多方向综合估计方法可降低估计误差,增加算法的稳定性.最后利用得到的点扩散函数和维纳滤波法进行图像重建.与现有算法的对比实验结果表明,针对适合大量成像系统的G类点扩散函数,本算法可以得到更准确的点扩散函数估计,且降低了振铃效应的影响,取得更好的图像复原效果.     

去除脑电信号眨眼伪差的独立成分时域相关算法

针对脑电信号易受眨眼动作干扰的问题,提出了一个自动地去除眨眼伪差的独立成分时域相关算法.该算法使用独立成分进行分析,并分解脑电信号,然后利用眨眼伪差独立成分与某些导联的脑电信号之间在时域存在较大相关性的特点,计算每个独立成分与前额附近的5个导联(Fp1,Fp2,F3,F4,Fz)信号的相关值的累加值,并对该值进行排序,将具有最大值的独立成分识别为眨眼伪差独立成分,将其设置为0,最后重建干净的脑电信号.通过对脑电信号的去除伪差实验表明:眨眼伪差引起的干扰基本被消除,伪差检测算法的敏感度和特异度分别是97.7％和98.3％,同时该算法能有效保持脑电信号基本不变.     

Single image deblurring using novel image prior constraints

Single image deblurring is a highly ill-posed problem and requires to be regularized. Many common forms of image prior have a major drawback that is unable to make full use of local image information. In this paper, we propose a single image deblurring method using novel image prior constraints. We establish a probabilistic model by enforcing inspired image prior constraints and adopt an advanced iterative scheme that alternates between blur kernel estimation and non-blind image restoration. To suppress ringing artifacts caused by inevitable blur kernel estimated errors, our method employs total variation image restoration and presents an alternation half-quadratic algorithm to solve the non-convex cost function. Finally, experiments show that our method has good performance in suppressing ringing artifacts, and makes a good balance between alleviating staircase effects and preserving image details.