Defocus estimation from stroboscopic cryo-electron microscopy data

Defocus estimation is an important step for improving the resolution of single particle reconstructions. It can be troublesome to estimate the defocus from low-dose cryo-electron microscopy (cryo-EM) data, particularly if there is not sufficient contrast present in the Fourier transform of the micrograph. Most existing approaches estimate the defocus from the presence of Thon rings within the power spectrum, employing image enhancement techniques to highlight these rings. In this paper, an approach to estimating the defocus from a stroboscopic image series is described. The image series is used to obtain two statistical metrics: figure of merit (FOM) and Q-factor. These metrics have been used to estimate the defoci from low-dose stroboscopic cryo-EM data consisting of a variable number of images.     

The microcomputer and image analysis in diagnostic pathology.

This paper presents a snapshot view of the influence and direction of microcomputer technology for image analysis techniques in diagnostic pathology. Microcomputers have had considerable impact in bringing image analysis to wider application. Semi-automated tracing techniques are a simple means of providing objective data and assist in a wide range of diagnostic problems. From the common theme of reducing subjectivity in diagnostic assessment, an extensive body of research has accrued. Some studies have addressed the need for quality control for reliable, routine application. Video digitizer cards bring digital image analysis within the reach of laboratory budgets, providing powerful tools for investigation of a wide range of cellular and tissue features. The use of staining procedures compatible with quantitative evaluation has become equally important. As well as assisting scene segmentation, cytochemical and immunochemical staining techniques relate the data to biological processes. With the present state of the art, practical use of microcomputer based image analysis is impaired by limitations of information extraction and specimen throughput. Recent advances in colour video imaging provide an extra dimension in the analysis of multi-spectral stains. Improvements will also be felt with predictable increase in speed of microprocessors, and with single chip devices which deliver video rate processing. If the full potential of this hardware is realized, high-speed, routine analysis becomes feasible. In addition, a microcomputer imaging system can play host to companion functions, such as image archiving and transmission. With this outlook, the use of microcomputers for image analysis in diagnostic pathology is certain to increase.(ABSTRACT TRUNCATED AT 250 WORDS)     

压电驱动器迟滞非线性的分数阶建模及实验验证

存在于压电陶瓷全工作范围内的迟滞非线性特性,往往会导致压电陶瓷执行器的系统精度下降、振荡,甚至造成系统的不稳定。针对周期性的正弦输入信号,提出一种基于分数阶算子的迟滞建模方法。首先,在分析压电特性和分数阶算子特性的基础上,采用结构简单参数少的分数阶算子来描述压电陶瓷的迟滞特性;然后,搭建了基于dSpace的压电驱动微位移定位实验平台;最后,将基于分数阶算子的迟滞建模方法应用于压电驱动微位移定位平台中,对压电陶瓷的迟滞非线性特性进行辨识。实验结果表明采用基于分数阶的迟滞模型(FOM)比传统的Prandtl-Ishlinskii模型(PIM)及其改进的增强型Prandtl-Ishlinskii模型(EPIM)更有优势;在低频段,FOM模型比PIM模型和EPIM模型精度略有提高,但是在高频段,FOM模型比PIM模型和EPIM模型精度则提高显著。在输入频率为100HZ的情况下,所提出的FOM模型较PIM模型的均方根误差(RMSE)值精度提高69.84%,较EPIM模型的RMSE值精度提高68.88%。     

Plasmonic Biosensor in NIR with Chalcogenide Glass Material: On the Role of Probe Geometry,Wavelength, and 2D Material

Samarium doped chalcogenide core, perfluorinated polymer clad with Ag metal and plasmonic 2D materials based plasmonic fiber-optic sensor is simulated and analyzed in near-infrared (NIR) wavelength regime. Proposed sensor is directed at the detection of the malignancy stages of liver tissues. The performance analysis (in terms of figure-of-merit, i.e., FOM) was carried out taking into account the MoS₂ and graphene monolayers as performance enhancing 2D materials. The analysis suggests that FOM values of MoS₂-based sensor probe are better than graphene-based probe. Further, a comparative study shows that fiber-optic probe is able to provide much better performance than prism-based probes. The FOM gets better for longer wavelength. The specificity of the biosensor can be improved by employing a suitable buffer layer (1–15 nm) as a bio-recognition element.     

The application of a normalized correlation function in image analysis

This paper describes the use of normalized correlation functions, such as auto- and cross-correlation functions for the analysis of images. The normalization is introduced to avoid problems of interpretation of the resulting correlation functions caused by the finite dimension of the image used for calculation. Due to a reduction of noise in the correlation function it is possible to detect periodic structures, which are hidden by noise in the original image. Besides the normalization of the correlation functions, a modification of the correlation function by periodic continuation of the image is proposed. This leads in all cases where the structure allows this to a further drastic reduction of noise. Besides the two-dimensional correlation functions one-dimensional correlation functions are proposed. It is shown that there are cases where it is difficult to find an adequate interpretation of these one-dimensional functions.     

基于FPGA的红外图像实时采集系统设计与实现

通过数字图像处理检测驾驶疲劳是一种具有高实用价值的非接触式疲劳检测方法,但目前相关研究多在理论算法范畴.提出直接采用单片FPGA芯片作为核心器件,生成精简的最小系统用以采集红外视频图像.详细阐述了此类视频采集系统的设计要点,从技术上实现了驾驶员红外图像的实时采集,存储和显示功能,配合直接实现于FPGA片上的数字图像算法即可在线实现驾驶疲劳检测.其电路系统结构精简,集成度高,灵活性强,配合不同的处理算法,可推广应用于军事、工业监控、医疗卫生等领域.     

A model for logarithmic image processing

Up to now, image processing and image analysis techniques have borrowed their basic tools from functional analysis: Fourier filtering, differential and integral calculus, and so on. These tools, however, only realize their efficiency when they are put into a well-defined algebraic frame, most of the time of a vectorial nature. Unfortunately, the class of functions modelling ‘images’, commonly referred to as ‘grey tone functions’ does not necessarily present this very type of structure. We present here an operation for the ‘addition’ of two images, with a physical justification in the context of transmitted light. Such an addition permits the construction of the family of ‘positive homothetics' of the grey tone function at hand. The vectorial context sought is well defined: The class of images associated with the class of their grey tone functions naturally becomes the positive cone of an ordered real vector space. Furthermore, the proposed model holds for logarithmic imaging and is compatible with what is known about the human visual process. This model has been called ‘LIP’ (logarithmic image processing model).     

A new edge detection method for automatic visual inspection

This paper presents a new edge-detection method which, based on simple arithmetic and logical operations, consists of three procedures: image binarisation, image contraction, and image subtraction. Experiments showed that the proposed algorithm could generate a path one pixel wide with continuous edges, and the proposed algorithm had a better edge-detection accuracy than the 4-connected, 8-connected, and the Sobel techniques. Therefore, the proposed edge-detection algorithm is feasible for use in automatic visual inspection systems.     

Three-dimensional molecular distribution in single cells analysed using the digital imaging microscope

Cellular changes in molecular distribution are believed to underly a wide range of cell functions. In order to investigate changes in molecular distribution in single cells utilizing fluorescent probes we have developed a digital imaging microscope. The system, consisting of both hardware and software, automatically acquires 3-D data sets consisting of optical sections and then processes such data to facilitate the analysis of molecular distribution in single cells. The first major step in processing reverses distortion introduced principally by the optics of the fluorescent microscope. Various procedures for accomplishing this task are compared and a method based on regularization theory is shown to give superior results for several different 3-D images. Following this step features of interest are automatically extracted from 3-D images utilizing an artificial 3-D visual system. This artificial visual system utilizes a system of spatial filters to identify regional characteristics of images, the information obtained from these filters being used to identify and characterize clusters of molecules within the image. This information is then utilized to construct a 3-D graphical model of molecular distribution in single cells. Such models are displayed in 3-D and may be further analysed utilizing interactive 3-D computer graphics. These methods are illustrated by results obtained regarding alpha-actinin distribution in single smooth muscle cells.     

一种灰度图像基本处理方法及实现方案

这是一种关于灰度图像处理的基本方法．尝试实现了对灰度图像的色阶处理．平滑处理、锐化处理及灰度调整等功能．设计了一套方便使用、针对性强的灰度图像处理软件，并给出了相应的算法代码和数学摸拟实现．实现了图像处理中的一些基本应用．因此可将该方法作为播件修改或添加到其它图像软件中，实现图像识别或模式匹配的预处理功能。