Two methods for semi-automated quantification of changes in ventricular volume and their use in schizophrenia

Two semi-automated methods for quantification of ventricular volume change from baseline and follow-up magnetic resonance imaging scans have been developed. Technique 1 employs direct segmentation of the ventricles from both the scans using thresholding and contour extraction. Technique 2 operates on difference images produced by voxel based intensity subtraction of the baseline from the registered follow-up images. Here, all voxels with intensities above a noise threshold and in a restricted area are monitored to compute volumetric changes. In phantom measurements the first technique was accurate to 0.0046%, the second to 0.167% of the phantom volume. Results from normal volunteers was that the average ventricular volume changed by 1.52% and 1.54% for images acquired within 9 months using techniques 1 and 2, respectively. With schizophrenic patients mean change of 10.78% and 9.43% were found employing the first and second procedures, respectively. All measurements agreed with a radiologist’s visual grading of the changes. Robust, objective, fast, easy-to-use, and fairly accurate procedures have been developed and validated to quantify volumetric changes.     

胃癌AgNOR银染色的定量分析研究

应用银胶染色法和计算机图像分析技术,对48例胃粘膜活检标本的石蜡切片进行Ag-NOR形态、定量分析研究。结果表明其对于区别胃疾患的良恶性和判定胃癌的分化程度有重要意义。     

高分辨阿达玛变换显微荧光图像分析(Ⅱ)单细胞DNA荧光图像生成、处理及自动定量分析研究

本研究把荧光显微镜，阿达玛变换多通道成像技术和计算机图象处理技术结合起来，建立了一种单细胞DNA荧光图像自动定量分析系统，对系统的成像原理、信号编码和解码方法及单细胞定量分析方法进行了讨论，分析结果表明，本系统提供的单细胞定量分析数据稳定可靠。     

应用普通扫描仪作薄层色谱定量分析的初步研究

尝试应用普通扫描仪作薄层色谱定量分析。样品通过硅胶板层析展开后，用碘蒸汽显色，再用普通扫描仪记录其图像，通过图像分析技术计算出斑点中样品的量。结果表明，对油醇、油酸、月桂胺和焦谷氨酸油酯等长碳链有机化合物，样点在nmol级的范围内时计算量与实际量有良好的线性相关性。     

Image analysis in the electron microscopy of cellulose protofibrils II. Digital correlation methods

Electron micrographs of parallel arrays of negatively stained ramie cellulose protofibrils were analyzed using the two-dimensional digital autocorrelation function (ACF). The method is based upon the statistical analysis of images in real space. The ACF shows strong parallel streaks of high correlation, and the lateral distance between adjacent streaks allows the mean interfibrillar distance to be estimated as 3.7 nm. The intensity profile along the streaks shows a weak modulation with peaks occurring at integral multiples of 3 or 6 nm. These results provide direct evidence that there is a regular axial texture in the protofibrils, and corroborate the conclusions previously drawn from optical diffraction analysis. Using the difference vectors found in the ACF it has been possible to reduce the picture noise level by linear integration, thereby obtaining an enhanced image. A preliminary result obtained in this way suggests that the projected protofibril morphology associated with the observed axial periodicity is a ribbon-like zigzag structure. Possible applications of the method for future work are discussed.     

Mathematical studies of Kekulé structures

The perfect matching vector and forcing and the Kekulé-vector of cata-benzenoids are defined. Two theorems are given which set the sufficient and necessary conditions for HKZ-vector (Harary et al. J Math Chem 6:295, 1991) and Kekulé-vector in cata-benzenoids. Additional two theorems are obtained which give sharp bounds for the modules of HKZ- and Kekulé vectors. Dedicated to Professor Tadeusz Marek Krygowski on the happy occasion of his 70th birthday.     

On the Randić Index of Acyclic Conjugated Molecules

The Randić index of an organic molecule whose molecular graph is G is the sum of the weights (d(u)d(v))^−1/2 of all edges uv of G, where d(u) and d(v) are the degrees of the vertices u and v in G. We give a sharp lower bound on the Randić index of conjugated trees (trees with a perfect matching) in terms of the number of vertices. A sharp lower bound on the Randić index of trees with a given size of matching is also given Mei Lu: Partially supported by NNSFC (No. 60172005) Lian-zhu Zhang: Partially supported by NNSFC (No. 10271105) Feng Tian: Partially supported by NNSFC (No. 10431020)     

Differential thermal analysis of the Al+20% (Fe-50%B) system

In the present study, aluminium and mechanically alloyed (36 h) Fe/B (50 wt%) are mixed. Al+20 (wt%) Fe/B mixture has been studied by differential thermal analysis to determine the aluminium quantity that is supposed to melt and afterwards does not solidify as it reacts with Fe/B powder. The different areas between endothermic reaction (melting peak) and exothermic reaction (solidification peak) allow in knowing the quantity of aluminium that reacts with Fe/B and the amount of intermetallic phases formed at high temperature. In order to follow the process, compacts were sintered at different temperatures (700, 800, 900, 1000 and 1200 °C), in N₂/10H₂/0.1CH₄ atmosphere. Microstructure was evaluated by image analysis and the results obtained by both techniques are compared.     

Performance of quantitative analyses by liquid chromatography–electrospray ionisation tandem mass spectrometry: from external calibration to isotopomer-based exact matching

Liquid chromatography–tandem mass spectrometry (LC-MS/MS) is a versatile coupling system which combines both selectivity and sensitivity and certainty. Hence, it is generally considered as the most reliable technique to quantify chemical compounds in complex matrices. In the present paper, we evaluate the performance of LC-MS/MS methods for the quantification of 3-nitrotyrosine in human urine in order to point out its dependence on the design of the quantification method, and emphasize the role of matrix effects in the performance. We compare external and internal calibrations, isotope dilution and isotopomer-based exact matching. The role of both sample preparation and multiple transitions monitoring is particularly addressed.     

基于深度学习的红外与可见光图像融合综述

图像融合技术是指从不同的源图像中提取并融合互补的信息,生成一幅信息量更丰富、对后续高级视觉任务提供足够支持的图像.红外与可见光图像融合（Infrared and Visible Image Fusion,IVIF）是图像融合领域的一个重要分支.近年来,深度学习技术在视觉计算领域表现出了良好的性能,尤其是基于自编码器、卷积神经网络、生成对抗网络等几种基于深度学习的IVIF技术得到了蓬勃发展.为此,对基于深度学习的IVIF算法的方法、数据集和评估指标等进行了总结和阐述;通过大量的实验,进行定性和定量的结果分析,对比了各类基于深度学习IVIF算法的性能;最后,讨论了该领域未来发展的一些前景和研究方向.