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。     

基于图像处理的树叶面积测量系统

以数字图像处理技术为基础,对数码相机拍摄的含有参照硬板和树叶的照片进行图像分析处理,提出了获取树叶的实际面积测量系统的一种独特实现方案。采用此方案开发出相应的应用软件,应用于树叶面积的测量计算,获得十分满意的结果。     

基于多小波的胃癌病理细胞图像边缘检测与分析

对胃癌细胞图像的多尺度小波变换边缘检测进行了研究,为医生运用现代信息理论的方法进行相关疾病诊断提供了一种新的思路和途径。提出了多尺度小波边缘检测的新方法,归纳了改善小波边缘检测效果的一些策略。实验结果表明,对于具有复杂纹理的医学病理细胞图像,采用传统的边缘检测方法会产生伪边缘和方向性误差,它影响了图像边缘检测的可信度;而运用小波变换的时频尺度特性和对奇异变化的优良检测性能,可得到无噪声污染的图像实际边缘。     

血液疾患与细胞粘附分子

血液疾患与细胞粘附分子阎有功,马丽瑛（广州军区武汉总医院检验科,武汉）（卫生部武汉卫生检疫局,武汉４３００６０）关键词细胞粘附分子,造血,血液疾患多细胞生物存在精细的细胞间网状结构,它与细胞相互接触、传递细胞内信息有关,这些结构称为细胞粘附分子（ＣＡ...     

豚鹿血液细胞和血液化学指标测定

应用Sysmex F-820血球计数仪和Olympus AU400全自动生化分析仪,对成都动物园圈养的16只豚鹿的46个血液样本进行血液细胞及血液化学43项指标检测,并对成体、亚成体及幼体进行统计分析,建立了一个参考指标.这对豚鹿的疾病诊断和繁育研究具有重要的意义.     

重庆地区圈养白唇鹿血液细胞和血液化学指标测定

白唇鹿(Cervus albirostris),别名白鼻鹿,属偶蹄目,鹿科,为我国特有珍稀濒临动物。野生群仅分布于我国海拔3500~5000 m青藏高原,被誉为高原神鹿。近年来由于人类的乱捕滥杀和环境的破坏趋于濒临灭绝,列为我国Ⅰ级保护动物[1,2]。白唇鹿具有重要的科学研究和较高的移地保护与展出观赏价值。重庆动物园引入一批白唇鹿进行移地保护并展出观赏,但由于白唇鹿是典型的高寒动物,在低海拔、高温、高湿的重庆地区饲养,生活环境和栖息场所均有一定改变,其生理功能将发生一定的变化。为此我们对入园近1年的白唇鹿进行了血液学分析,以期为白唇鹿的人工…     

DC-CIK细胞的生物学活性及体外抗血液肿瘤研究

目的:研究细胞因子诱导的杀伤细胞(CIK)与树突状细胞(DC)共培养后的体外增殖能力、免疫表型变化、分泌细胞因子水平以及对K562、K562/ADM细胞毒作用的影响.方法:正常人外周血单个核细胞诱导DC和CIK细胞,将DC与CIK共培养,以CIK细胞单独培养为对照.用台盼蓝活细胞计数计算细胞扩增倍数,MTT法测定杀伤活性,流式细胞术分析免疫表型,ELISA双抗体夹心法检测分泌干扰素-γ(IFN-γ)、白细胞介素-12(IL-12)的水平.结果:DC-CIK细胞增殖能力明显高于CIK细胞(P＜0.05);DC、CIK细胞共培养后,CD3+ CD8+、CD3+ CD56+双阳性细胞比率较同条件下CIK细胞组显著增多(P＜0.05);共培养3d,DC-CIK细胞上清液中IL-12、INF-7的分泌量均比CIK细胞单独培养的分泌量高(P＜0.01,P＜ 0.05);在2.5∶1-20∶1的效靶比范围内,DC-CIK共培养物对K562和K562/ADM的杀伤活性均高于单纯CIK细胞组,且差异显著(P＜0.05),且杀伤率与效靶比呈正相关.结论:DC-CIK细胞的增殖能力、分泌细胞因子水平、对K562和K562/ADM的杀伤活性均高于CIK细胞,为DC-CIK细胞免疫治疗提供了实验和理论依据.     

基于分段伪氨基酸组成成分特征提取方法预测蛋白质亚细胞定位

蛋白质的亚细胞定位与蛋白质的功能密切相关,其定位预测有助于人们了解蛋白质功能.文章提出一种分段伪氨基酸组成成分特征提取方法,采用支持向量机算法对Chou构建的两个蛋白质亚细胞定位数据集(C2129,CS2423)进行了分类研究,并采用总分类精度Q3、内容平衡精度指数Q9等参数评估预测分类系统性能.预测结果表明,基于分段伪氨基酸组成成分特征提取方法的预测性能,优于基于完整蛋白质序列的伪氨基酸组成成分特征提取方法.例如,基于分段矩描述子伪氨基酸组成成分特征提取方法,数据集C2129的Q3和Q9分别为84.7%和60.8%,比基于完整蛋白质序列的矩描述子伪氨基酸组成成分特征提取方法分别提高1.8和2.2个百分点,且Q3比现有Xiao等人的方法提高了9.1个百分点.基于分段伪氨基酸组成成分特征提取方法构成的特征向量不仅包含残基之间的位置信息,而且还包含蛋白质子序列之问的耦合信息,另外蛋白质分段子序列可能和蛋白质的功能域有一定的联系,从而使这一方法能够有效地预测蛋白质亚细胞定位.     

孔雀传染性喉气管炎的血液细胞分析

本文对13只传染性喉气管炎(ILT)发病孔雀和9只正常健康孔雀做了血液细胞分析和比较,结果表明ILT孔雀的WBC总数、LYM的百分数高于正常健康孔雀,而RBC总数、HGB、MCH、PLT和MID、GRA的百分数均低于后者,特别是PLT呈极显著差异,为科学认识和临床诊断该病提供了重要依据。     

基于改进型组织特异纹理滤波器的乳腺肿瘤超声图像处理

基于乳腺超声图像的多参数纹理分类实验,改进了Gjenna Sfippel等的自适应纹理滤波器,通过引入模糊函数、增加重叠区域和迭代次数的措施,在减少图像噪声的同时,增强肿瘤与周围正常组织的视觉差别。量化比较乳腺超声图像经该滤波算法和几种常用滤波算法处理前后的的统计特征参量和肿瘤边缘检测的精确率,验证了该算法的有效性和优越性。     

Deep learning-based image processing in optical microscopy

Optical microscopy has emerged as a key driver of fundamental research since it provides the ability to probe into imperceptible structures in the biomedical world. For the detailed investigation of samples, a high-resolution image with enhanced contrast and minimal damage is preferred. To achieve this, an automated image analysis method is preferable over manual analysis in terms of both speed of acquisition and reduced error accumulation. In this regard, deep learning (DL)-based image processing can be highly beneficial. The review summarises and critiques the use of DL in image processing for the data collected using various optical microscopic techniques. In tandem with optical microscopy, DL has already found applications in various problems related to image classification and segmentation. It has also performed well in enhancing image resolution in smartphone-based microscopy, which in turn enablse crucial medical assistance in remote places.Graphical abstract     

Feature extraction and signal processing for nylon DNA microarrays

Background  

High-density DNA microarrays require automatic feature extraction methodologies and softwares. These can be a potential source of non-reproducibility of gene expression measurements. Variation in feature location or in signal integration methodology may be a significant contribution to the observed variance in gene expression levels.     

基于希尔伯特-黄变换的核小体定位特征提取

核小体是染色体折叠的整体结构,它们的空间分布与基因组活动的调节密切相关,是基因工程和表观遗传的重要研究领域。为进一步研究核小体定位特征的物种间差异性,将希尔伯特-黄变换(HHT)引入到酵母和果蝇两个不同物种的定位信号中,从多个角度客观分析核小体定位信号特征在两个物种间的差异性。在此基础上,对酵母和果蝇核小体分布的周期特征和进化印记进行尺度和频域分析,结果表明酵母和果蝇染色体在组织结构上存在显著差异。本文研究思路为准确提取信号瞬时频率提供了前提条件。     

一种新型的基于图像的DNA序列可视化模型

传统的DNA序列可视化模型局限于短DNA序列的可视化,并且缺乏对可视化图形的通用分析方法。因此,文章提出了一种基于图像的DNA序列可视化模型,这种模型通过将一维的DNA序列转换为二维的256色的灰度图像,可以实现长DNA序列的可视化,具有很高的空间紧密性。借助成熟的图像处理方法来分析DNA可视化图像,可以获取原始DNA序列的规模、4种不同碱基的分布、无序程度等重要信息。通过比较不同DNA序列的可视化图像,可以获取这些序列的相似性信息。     

Morphological characterisation of yeast colony growth on solid media using image processing

To rapidly determine the effect of environmental factors on yeast growth, a cell counting and colony sizing image analysis method was developed to characterise colony growth on solid media. A digitised microscopic image of the yeast was analysed using the Watershed algorithm for cell number determination and a morphological edge detection for colony size determination. The influence of temperature and physiological stress on yeast growth was then investigated over 12.5 h and data extracted by the image analysis method. © Rapid Science Ltd. 1998     

New technologies for automated cell counting based on optical image analysis `The Cellscreen'

A prototype of a newly developed apparatus for measuring cell growth characteristics of suspension cells in micro titre plates over a period of time was examined. Fully automated non-invasive cell counts in small volume cultivation vessels, e.g. 96 well plates, were performed with the Cellscreen system by Innovatis AG, Germany. The system automatically generates microscopic images of suspension cells which had sedimented on the base of the well plate. The total cell number and cell geometry was analysed without staining or sampling using the Cedex image recognition technology. Thus, time course studies of cell growth with the identical culture became possible. Basic parameters like the measurement range, the minimum number of images which were required for statistically reliable results, as well as the influence of the measurement itself and the effect of evaporation in 96 well plates on cell proliferation were determined. A comparison with standard methods including the influence of the cultured volume per well (25 l to 200 l) on cell growth was performed. Furthermore, the toxic substances ammonia, lactate and butyrate were used to show that the Cellscreen system is able to detect even the slightest changes in the specific growth rate.     

A new image processing technique for determination of cell-generated deformations on substrata

This paper introduces a new image processing technique that determines the displacement field of a given substrate from “null-force” and “force-loaded” images. In this method, fluorescent elements used to track motion, which will be referred to as beads, can be seen in these images by locating the gray value that is normally distributed around their central point. Next comes a two-step process of matching the beads with displacements. The first step matches the beads with a small displacement using the correlation function of the characteristic pixels. Based on results from this initial step, another correlation function determines a pair of beads with a relatively large displacement. The entire matching process is done in this way, gradually working from the small displacement to the large one. Finally, using the cubic spline weight function, the whole displacement field is interpolated and filtered out of those displacements, which were initially found with the matched beads. Applying this new method on the cell migration yields satisfying results. Based on the particle tracking, the displacement field obtained by this new image processing technique has clear physical meaning. More importantly, this new method completes the matching of the displacement using the features of the displacement field, thus avoiding the direct matching with the image gray values for the relatively large strain of the substrate around the cell. Accordingly, it greatly decreases mismatching, making data checking unnecessary.     

基于邻接矩阵分解的肿瘤亚型特征提取方法

基于肿瘤基因表达谱的肿瘤分类是生物信息学的一个重要研究内容。传统的肿瘤信息特征提取方法大多基于信息基因选择方法,但是在筛选基因时,不可避免的会造成分类信息的流失。提出了一种基于邻接矩阵分解的肿瘤亚型特征提取方法,首先对肿瘤基因表达谱数据构造高斯权邻接矩阵,接着对邻接矩阵进行奇异值分解,最后将分解得到的正交矩阵特征行向量作为分类特征输入支持向量机进行分类识别。采用留一法对白血病两个亚型的基因表达谱数据集进行实验,实验结果证明了该方法的可行性和有效性。     

Automated cell isolation from photodegradable hydrogel based on fluorescence image analysis

We report an automated cell-isolation system based on fluorescence image analysis of cell aggregates cultured in a photodegradable hydrogel. The system incorporates cell culture in a humidified atmosphere with controlled CO₂ concentration and temperature, image acquisition and analysis, micropatterned light exposure, and cell collection by pipetting. Cell aggregates were cultured on hydrogels, and target cells were selected by phase contrast and fluorescence image analysis. After degradation of the hydrogel by exposure to micropatterned UV light, cell aggregates were transferred to a collection vessel by robotic pipetting. We assessed the system for hydrogel degradation, recovery of target cells, and contamination by off-target cells. We demonstrated two practical applications of our method: (i) in cell aggregates from MCF-7-RFP strains in which 18.8% of cells produced red fluorescent protein (RFP), we successfully obtained 14 proliferative fluorescence-positive cell aggregates from 31-wells, and all of the isolated strains produced a higher proportion of RFP production than the original populations; (ii) after fluorescent immunostaining of human epidermal growth factor receptor 2 (HER2) in cancer cells, we successfully isolated HER2-positive cells from a mixed population of HER2-positive and -negative cells, and gene sequence analysis confirmed that the isolated cells mainly contained the target cells.