野生大豆和烟草根尖细胞分化过程中的DNA动态和细胞图像分析

分别截取野生大豆根尖分生区、伸长区和成熟区细胞,用Ｈｏｅｃｈｓｔ３３２５８对ＤＮＡ进行专一染邑,通过计算机数字图象处理系统,采用灰度测量法原位测定根尖不同区的ＤＮＡ含量。同理取烟草根尖不同区细胞,用率尔根反应对ＤＮＡ进行专一染色,并由与扫描显微光度计相联的数字图象处理系统原位测定备区域中细胞的ＤＮＡ含量。发现从分生区到成熟区,细胞核ＤＮＡ含量呈递增趋势。分化的细胞中含量异常增高而不分裂,说明ＤＮＡ的动态变化与发育和分化存在着某种联系。细胞图象分析的结果表明三个区的细胞面积、最大径、最小径及形态因子也沿分生区到成熟区呈递增趋势。     

LHRH刺激雄性大鼠垂体LH分泌高峰时细胞形态变化的图象分析

应用ＡＢＣ亲和组织化学顺序、ＭＩＳ－１计划机图象处理系统测定外源性ＬＨＲＨ刺激雄性大鼠ＬＨ分泌高峰前后ＬＨ细胞面积、细胞内液泡面积和细胞形状等形态参数的变化。结果表明：雄性大鼠ＬＨ基础分泌时,ＬＨ细胞处于贮存状态。     

时延细胞神经网络的全局稳定性分析

本文利用 Ｌｙａｐｕｎｏｖ泛函方法和一些分析技巧得到了一类时延细胞神经网络ＤＣＮＮ全局渐进稳定性的若干新的判据；这些判据可用于设计出全局稳定的各种动态网络，且在信号处理，特别是动态图象处理中具有重要的意义．     

红细胞低温显微动态图象处理技术的建立和应用研究

本文报道了一种新型的低温生物学实验系统——红细胞低温显微动态图象处理系统,该系统将先进的计算机控温、图象处理技术和低温显微镜及摄录象机有机地联成一体。将此技术应用于红细胞的低温冰冻保存实验,具有能实时记录血细胞在冰冻过程中的实验参数(如时间、温度、降温速率等)与细胞图象,能对其图象处理及面积、体积测量,也能使细胞呈现伪彩色及测定红细胞冰冻损伤程度。该系统是一新的综合性的低温生物学研究仪器,对研究器官保存与移植具有明显意义。     

鼻咽癌细胞双光子显微图像处理

鼻咽细胞的双光子显微图像中含有着丰富信息,借助计算机和图像处理算法可进行分析处理。图象分割是双光子显微图象处理中的一项重要技术,至今为止尚未形成一个最佳通用方法,也没有定义出双光子显微图象分割的统一标准。本文首先采用噪声干扰法进行去噪,采用低帽的变换等的数学形态学来增强鼻咽癌细胞图像,使细胞更加容易分辨,接着对几种经典边缘检测算法进行讨论比较,紧接着根据鼻咽双光子显微图像的实际特征,采取腐蚀算法求出鼻咽癌细胞边缘。然后进行区域生长定位细胞,并采用一些改进的判别分析算法和区域面积算法对鼻咽癌细胞进行阈值分割,获得较好结果。     

虎源猫泛白细胞减少症病毒的分离鉴定

利用细胞培养方法从中国某虎园送检的腹泻虎肠内容物中分离出1 株细小病毒(TPV/ HT - 69),经系统的形态学、理化学、血清学试验、人工感染试验、PCR 扩增和VP2 基因序列分析,符合猫泛白细胞减少症病毒特征,证明该毒株为猫泛白细胞减少症病毒强毒。     

无细胞蛋白质合成的研究进展

无细胞合成生物学作为新兴的多学科交叉手段,已很好地应用于蛋白质工程领域。因为无细胞生物合成系统无需完整的活细胞,在体外就可激活转录和翻译机器,因此,可减少对细胞的依赖性,从而增加工程的自由度。无细胞系统的这些优点使它已经成为强大的蛋白质工程平台,用于膜蛋白和医药蛋白的合成、非天然氨基酸的嵌入以及高通量分析。无细胞蛋白质合成系统不仅在基础科学研究而且在工业化生产中拥有广阔的应用前景。本文中,笔者系统综述了无细胞蛋白质合成系统的研究及应用,并展望了该系统的研究前景。     

细胞微系统技术及其应用

细胞微系统技术研究是目前细胞生物学、微系统科学及药物筛选等学科交叉领域的一个研究热点,其综合利用了微系统平台技术,将细胞的培养、观测和分析在微系统平台上完成,丰富了细胞研究方法,为细胞研究提供了一个全新的研究平台。现对目前细胞微系统研究中几种典型的方法,如立体微结构模型、软光刻、微流体、芯片毛细管电泳、微电极等进行综述,并阐述其在细胞生物学、生命科学等领域相关研究中的应用。     

神经生长因子介导的神经促生化合物筛选系统的建立

为了合理评价化合物的促神经再生活性.用(MTT)、分化计数、图象处理等方法,借助FK506、GPI1046阳性化合物,建立了一个基于PC12细胞存活和分化的化合物筛选系统.结果表明,无论在细胞存活实验还是在分化实验中,FK506、GPI1046都可以明显增强神经生长因子(NGF)的效应,即促神经再生的作用.也就是说,这一系统将有助于从组合化学方法合成的化合物文库中,筛选出具有促神经再生活性的化合物.     

细胞形态相关技术在血液系统肿瘤中的应用

细胞形态学检验是一门传统的血液病实验诊断技术,方便快捷,实用性强。细胞形态是病理诊断最直观的依据,但现行的普通光学显微镜镜检技术已不能完全满足血液肿瘤精准诊断的需求。如何开发研究或完善相关技术,最大发挥形态学的优势是值得探讨和研究的问题。系统阐述了细胞形态相关技术在血液系统肿瘤的早期诊断、疗效及预后评估及疾病复发等方面的应用研究进展,相信细胞形态相关技术必将为血液系统肿瘤的诊疗带来新的机遇。     

红细胞膜变形能力与胞内分子聚合状态和细胞形态的相关变化

以显微激光散射光谱和图像分析技术,对单个活态红细胞在无扰、在位、实时的情况下,测量了人血红细胞膜的变形能力,以及与之同时对应的胞内血红蛋白的聚合状态和细胞的形态结构。并据此研究了它们的相关关系及随各种生理条件而交互变化的情况。     

High Throughput Screening of Gene Expression Signatures

This paper focuses on microarray image analysis and discusses a completely automated approach to image processing, which eliminates human intervention. A system for automated image processing is described, which is capable of processing image files in a batch-mode thus allowing high-throughput of microarray image analysis. Grid-placement and spot finding are achieved without operator's help. The software eliminates noise signals from the data analysis process and minimizes operator's involvement in the procedure.     

声损伤后鸡听觉上皮的修复和毛细胞再生──扫描电镜与图像分析研究

应用扫描电镜和图像分析方法对宽带噪声损伤后鸡基底乳头病变以及听觉毛细胞再生反应进行定量研究。观察了存活０、２、７、１５和３０天时平均毛细胞表面积,平均毛细胞密度,毛细胞／支持细胞面积比及基底乳头损伤范围等参数。结果显示,基底乳头病变范围为近端１０％至中段６０％。早期反应包括支持细胞扩张和毛细胞静纤毛变性及皮板表面积缩小。损伤后２天可见新生毛细胞,形态与胚胎期幼稚毛细胞相似。７～１５天毛细胞数目与表面积逐渐增加,基底乳头ｍｏｓａｉｃ构型基本恢复。静纤毛排列与极性至３０天时尚未完全恢复。损伤区仍有散在的残存毛细胞及分化早期的幼稚毛细胞。上述结果提示,再生毛细胞的前体存在于受损区局部并与支持细胞的活动有关。前体细胞的增殖至再生毛细胞出现的时间约为４８ｈ,但亦存在一定程度的非同步现象,损伤后７～１５天为细胞修复的主要时期。     

Imaging system for morphometric assessment of absorption or fluorescence in stained cells

An image acquisition and processing system has been developed for quantitative microscopy of absorption or fluorescence in stained cells. Three different light transducers are used in the system to exploit the best characteristics of these sensors for different biological measurements. A digital scanner, in the form of a linear array charge-coupled device (CCD), acquires data with high spatial and photometric resolution. A color (RGB) camera is employed when spectral information is required for the segmentation of cellular subcomponents. An image-intensified charged-injection device (CID) camera provides for very low light intensity measurements, primarily for fluorescence-labeled cells. Properties of these transducers, such as contrast transfer function, linearity, and photo-response nonuniformity, have been measured. Two dedicated image processing units were incorporated into the system. The front-end processor, based on a digital signal processor, provides functions such as object detection, raw image calibration, compression, artifact removal, and filtering. The second image processor is associated with the frame memory and includes a histogram processor, a dedicated arithmetic logic unit for image processing functions, and a graphics module for one-bit overlay functions. An interactive program was developed to acquire cell images and to experiment with a range of segmentation algorithms, feature extractions, and other image processing functions. The results of any image operation are displayed on the video monitor. Once a desired processing sequence is determined, the sequence may be stored to become part of a command library and can be executed thereafter as a single instruction.     

Distributed computing in image analysis using open source frameworks and application to image sharpness assessment of histological whole slide images

Background

Automated image analysis on virtual slides is evolving rapidly and will play an important role in the future of digital pathology. Due to the image size, the computational cost of processing whole slide images (WSIs) in full resolution is immense. Moreover, image analysis requires well focused images in high magnification.

Methods

We present a system that merges virtual microscopy techniques, open source image analysis software, and distributed parallel processing. We have integrated the parallel processing framework JPPF, so batch processing can be performed distributed and in parallel. All resulting meta data and image data are collected and merged. As an example the system is applied to the specific task of image sharpness assessment. ImageJ is an open source image editing and processing framework developed at the NIH having a large user community that contributes image processing algorithms wrapped as plug-ins in a wide field of life science applications. We developed an ImageJ plug-in that supports both basic interactive virtual microscope and batch processing functionality. For the application of sharpness inspection we employ an approach with non-overlapping tiles. Compute nodes retrieve image tiles of moderate size from the streaming server and compute the focus measure. Each tile is divided into small sub images to calculate an edge based sharpness criterion which is used for classification. The results are aggregated in a sharpness map.

Results

Based on the system we calculate a sharpness measure and classify virtual slides into one of the following categories - excellent, okay, review and defective. Generating a scaled sharpness map enables the user to evaluate sharpness of WSIs and shows overall quality at a glance thus reducing tedious assessment work.

Conclusions

Using sharpness assessment as an example, the introduced system can be used to process, analyze and parallelize analysis of whole slide images based on open source software.

     

Morphometric requirements for image analysis and the IBAS interactive automatic image analysis system

The morphometric demands made on an image analysis system are discussed, as is the IBAS interactive automatic system, which meets those requirements. The modular design of the IBAS image analysis system, with its tailor-made processors for image processing, system control and pattern recognition, gives speed and flexibility. The IMAGE image analysis language guarantees user friendliness, and, last but not least, the enormous amount of software offers accurate, reproducible measurements and dedicated evaluation programs.     

Using digital image processing for counting whiteflies on soybean leaves

This paper presents a new system, based on digital image processing, to quantify whiteflies on soybean leaves. This approach allows counting to be fully automated, considerably speeding up the process in comparison with the manual approach. The proposed algorithm is capable of detecting and quantifying not only adult whiteflies, but also specimens in the nymph stage. A complete performance evaluation is presented, with emphasis on the conditions and situations for which the algorithm succeeds, and also on the circumstances that need further work. Although this proposal was entirely developed using soybean leaves, it can be easily extended to other kinds of crops with little or no changes in the algorithm. The system employs only widely used image processing operations, so it can be easily implemented in any image processing software package.     

Image analysis as a tool for quantitative phycology: a computational approach to cyanobacterial taxa identification

In the following work we discuss the application of image processing and pattern recognition to the field of quantitative phycology. We overview the area of image processing and review previously published literature pertaining to the image analysis of phycological images and, in particular, cyanobacterial image processing. We then discuss the main operations used to process images and quantify data contained within them. To demonstrate the utility of image processing to cyanobacteria classification, we present details of an image analysis system for automatically detecting and classifying several cyanobacterial taxa of Lake Biwa, Japan. Specifically, we initially target the genus Microcystis for detection and classification from among several species of Anabaena. We subsequently extend the system to classify a total of six cyanobacteria species. High-resolution microscope images containing a mix of the above species and other nontargeted objects are analyzed, and any detected objects are removed from the image for further analysis. Following image enhancement, we measure object properties and compare them to a previously compiled database of species characteristics. Classification of an object as belonging to a particular class membership (e.g., “Microcystis,”“A. smithii,”“Other,” etc.) is performed using parametric statistical methods. Leave-one-out classification results suggest a system error rate of approximately 3%. Received: September 6, 1999 / Accepted: February 6, 2000     

Objective method of comparing DNA microarray image analysis systems

Many image analysis systems are available for processing the images produced by laser scanning of DNA microarrays. The image processing system takes pixel-level intensity data and converts it to a set of gene-level expression or copy number summaries that will be used in further analyses. Image analysis systems currently in use differ with regard to the specific algorithms they implement, ease of use, and cost. Thus, it would be desirable to have an objective means of comparing systems. Here we describe a systematic method of comparing image processing results produced by different image analysis systems using a series of replicate microarray experiments. We demonstrate the method with a comparison of cDNA microarray data generated by the UCSF Spot and the GenePix image processing systems.     

2dx_merge: data management and merging for 2D crystal images

Electron crystallography of membrane proteins determines the structure of membrane-reconstituted and two-dimensionally (2D) crystallized membrane proteins by low-dose imaging with the transmission electron microscope, and computer image processing. We have previously presented the software system 2dx, for user-friendly image processing of 2D crystal images. Its central component 2dx_image is based on the MRC program suite, and allows the optionally fully automatic processing of one 2D crystal image. We present here the program 2dx_merge, which assists the user in the management of a 2D crystal image processing project, and facilitates the merging of the data from multiple images. The merged dataset can be used as a reference to re-process all images, which usually improves the resolution of the final reconstruction. Image processing and merging can be applied iteratively, until convergence is reached. 2dx is available under the GNU General Public License at http://2dx.org.