磁共振成像设备图像均匀性及层厚检测方法分析与评价

图像均匀性及层厚是磁共振成像设备进行质量控制的主要性能参数.文章利用美国体膜实验室生产的Magphan SMR100体膜对磁共振成像设备的图像均匀性及层厚进行计量检测,分析了影响图像均匀性的各种因素以及图像不均匀对层厚测量带来的偏差,从而提高对磁共振成像设备周期检定的实践水平,确保磁共振成像设备图像清晰、可靠.     

单张纸平版印刷机压力均匀性与稳定性的测量方法

平版印刷机压力均匀性与稳定性直接影响印刷质量,是印刷机的重要评价指标.文章叙述了平版印刷机(胶印机)印力均匀性与稳定的测量方法,举例说明了测量过程,并对测量数据进行了不确定度评定.     

薄壁回转曲面壁厚的测量方法

介绍一种公差尺寸小薄壁且为回转曲面工件壁厚测量的方法,并对该测量方法进行了不确定度分析。该测量方法具有不确定度高、易于操作、适用于大批量测量的特点。     

等厚干涉数字处理系统研究与测量

将CCD和计算机图像处理技术融入到等厚干涉仪测量系统中,实现测量过程自动化,数据处理微机化,降低劳动强度,提高测量效率和测量准确定。     

齿厚卡尺综合误差测量结果的不确定度评定

文章介绍了齿厚卡尺综合误差测量结果不确定度的评定方法,解决了校准规范中没有不确定度分析的问题。     

恒温槽温度均匀性测量值的不确定度评定

本文介绍恒温槽温度均匀性测量值的不确定度评定方法。     

高精度平面度测量方法的研究

本以中等尺寸０００级平板为研究对象,采用双频激光测量系统的直线度测量部件进行平面度测量,分析计算了这一测量方法的测量不确定度,并进行了实际测试。     

小管径壁厚超声测量方法及测量不确定度分析

导管等管状类零件是飞机、发动机等产品的重要构件,这类构件承担着输送燃油、液压、氧气、冷气等任务,处于承压工作状态,需要保证零件的强度,才能保证产品的使用安全,壁厚作为直接影响强度的指标,通常对于其最小厚度有着严格的控制要求。但是常用的超声测厚在实际的小管径厚度现场测量时会出现测量数据不稳定甚至无法显示厚度数据的现象,导致超声测厚数据无法作为厚度评价依据。论文针对小管径管状类零件壁厚超声测量难题,通过对超声测厚机理的分析,提出频率、换能器直径、延迟块外形、换能器夹持工装等方面的改进建议,从而获得稳定有效的测量数据。同时对改进后的超声测厚提出基于蒙特卡洛方法的测厚不确定度分析方法,并通过试件进行测量不确定度的分析、评定,供从事小管径壁厚超声测量的检测人员参考。     

复现性不确定度的计算

复现性不确定度是不确定度的重要部分,本文探讨了它的方差分析计算法与综合计算法,详细讨论了计算性质,最后举出了应用实例。     

Analytical methods for characterizing magnetic resonance probes

The efficiency of Gd(III) contrast agents in magnetic resonance image enhancement is governed by a set of tunable structural parameters. Understanding and measuring these parameters requires specific analytical techniques. This Feature describes strategies to optimize each of the critical Gd(III) relaxation parameters for molecular imaging applications and the methods employed for their evaluation.     

Optoelectronic parallel watershed implementation for segmentation of magnetic resonance brain images

An optoelectronic implementation for the morphological watershed transform is proposed. Fiber-optic programmable logic arrays are used in the implementation because of their high fan factors at high clock speeds. Image segmentation is one of the main applications of the watershed transform. Based on the optoelectronic implementation, an algorithm for the segmentation of axial magnetic resonance (MR) head images to extract information on brain matter is presented. Simulation results for the different steps of the segmentation process are presented.     

Classification of magnetic resonance images from rabbit renal perfusion

The feasibility of using chemometric techniques for the automatic detection of whether a rabbit kidney is pathological or not is studied. Sequential images of the kidney are acquired using Dynamic Contrast-Enhanced Magnetic Resonance Imaging with contrast agent injection. A segmentation approach based upon principal component analysis (PCA) is used to separate out the cortex from the rest of the kidney including the medulla, the renal pelvic, and the background. Two classifiers (Soft Independent Method of Class Analogy, SIMCA; Partial Least Squares Discriminant Analysis, PLS-DA) are tested for various types of data pre-treatment including segmentation, feature extraction, centering, autoscaling, standard normal variate transformation, Savitsky-Golay smoothing, and normalization. It is shown that (i) the renal cortex contains more discriminating information on kidney perfusion changes than the whole kidney, and (ii) the PLS-DA classifiers outperform the SIMCA classifiers. PLS-DA, preceded by an automated PCA-based segmentation of kidney anatomical regions, correctly classified all kidneys and constitutes a classification tool of the renal function that can be useful for the clinical diagnosis of renovascular diseases.     

Neural network approach to segmentation of magnetic resonance head images

A novel image segmentation scheme based on a neural network has been implemented to segment magnetic resonance head images. A three-layer perceptron-type neural network, trained with backward error propagation algorithm was used. The scheme utilizes first-echo intensity and computed T₂ values to construct a two-parameter space for classification. After training on a selected slice, the method successfully segments all slices for a given subject without any further human interaction.     

A fast and accurate algorithm for a Galerkin boundary integral method

A fast and accurate algorithm is presented to increase the computational efficiency of a Galerkin boundary integral method for solving two-dimensional elastostatics problems involving numerous straight cracks and circular inhomogeneities. The efficiency is improved by computing the combined influences of groups, or blocks, of elements—with each element being an inclusion, a hole, or a crack—using asymptotic expansions, multiple shifts, and Taylor series expansions. The coefficients in the asymptotic and Taylor series expansions are computed analytically. Implementation of this algorithm involves a single- or multi-level grid, a clustering technique, and a tree data structure. An iterative procedure is adopted to solve the coefficients in the series expansions of boundary unknowns block by block. The elastic fields in each block are calculated by superposition of the direct influences from the nearby elements and the grouped far-field influences from all the other elements. This fast multipole algorithm is considerably more efficient for large-scale practical problems than the conventional approach.     

轮胎滚动阻力精确测试方法研究

针对目前常用的轮胎滚动阻力室内测试方法(测力法、滑行法、反拖法等)与室外实际道路得出的轮胎滚动阻力对比相差较大的问题,通过比较分析各种现有测试方法的优缺点,提出一种利用单滚筒底盘测功机来测量轮胎滚动阻力的方法。为提高测试准确度,在实验开始前依据转鼓自身滑行消除单滚筒台架的内阻,在单滚筒底盘测功机的无加载滑行和二次加载滑行实验基础之上建立相应的数学模型,得出汽车和测功机总的惯性质量,具有操作简单、准确度高等优点。     

Iron-based magnetic nanoparticles for magnetic resonance imaging

Magnetic resonance imaging (MRI) has been an extensive area of research owing to its depth of penetration for clinical diagnosis. Signal intensity under MRI is related to both T₁, spin-lattice relaxation, and T₂, spin-spin relaxation. To increase the contrast variability under MRI, several contrast agents are being used, i.e. T₁ contrast agents (e.g. gadolinium) and T₂ contrast agents (e.g. iron-based magnetic nanoparticles). These contrast agents are administered prior to scanning to increase contrast visibility. They reduce the T₁ and T₂ relaxation times to produce hyperintense and hypointense signals, respectively. Tunable properties of iron-based magnetic nanoparticles and several coating materials provide a platform to get superb MRI contrast in T₂ weighted images. It has been found that contrast enhancement by iron-based magnetic nanoparticles is dependent on the size, shape, composition, surface, and magnetic properties which can be tuned with the synthesis method and coating material. Therefore, understanding the synthesis method and properties of magnetic nanoparticles is vital to contribute to MR signal enhancement which is directing the scientist to design engineered iron-based magnetic nanoparticles. This paper introduces the concept of MRI contrast enhancement. We mainly discuss the synthesis of T₂ contrast agents, i.e. iron-based magnetic nanoparticles and the modification of these T₂ contrast agents by coating followed by their biomedical applications.     

Dynamic windowing algorithm for the fast and accurate determination of luminescence lifetimes

An algorithm for the accurate calculation of luminescence lifetimes in near-real-time is described. The dynamic rapid lifetime determination (DRLD) method uses a window-summing technique and dynamically selects the appropriate window width for each lifetime decay such that a large range of lifetimes can be accurately calculated. The selection of window width is based on an optimal range of window-sum ratios. The algorithm was compared to alternative approaches for rapid lifetime determination as well as nonlinear least-squares (NLLS) fitting in both simulated and real experimental conditions. A palladium porphyrin was used as a model luminophore to quantitatively evaluate the algorithm in a dynamic situation, where oxygen concentration was modulated to induce a change in lifetime. Unlike other window-summing techniques, the new algorithm calculates lifetimes that are not significantly different than the slower, traditional NLLS. In addition, the computation time required to calculate the lifetime is 4 orders of magnitude less than NLLS and 2 orders less than other iterative methods. This advance will improve the accuracy of real-time measurements that must be made on samples that are expected to exhibit widely varying lifetimes, such as sensors and biosensors.