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金探测器:一种用于在电子显微镜图像中快速自动进行双金标记检测、计数和颜色叠加的计算机方法。

Gold finder: a computer method for fast automatic double gold labeling detection, counting, and color overlay in electron microscopic images.

作者信息

Monteiro-Leal Luiz Henrique, Troster Helmut, Campanati Loraine, Spring Herbert, F Trendelenburg Michael

机构信息

Universidade do Estado do Rio de Janeiro, Dept. de Histologia e Embriologia, Laboratório de Microscopia e Processamento de Imagens, Av. Prof. Manoel de Abreu, 48 3 degrees andar. Maracanã, 20550-170, Rio de Janeiro, RJ, Brazil.

出版信息

J Struct Biol. 2003 Mar;141(3):228-39. doi: 10.1016/s1047-8477(02)00624-x.

Abstract

This work presents a computerized method to identify, detect, evaluate, and, by colored overlay, present gold particle pairs in electron microscopy (EM), even in wide-field views. Double gold immunolabeled specimens were analyzed in a LEO 912 electron microscope equipped with a 2k x 2k-pixel slow-scan cooled CCD camera connected to a computer with analySIS 3.1 PRO image processing software. The acquisition of a high-resolution and high-dynamic-range image by the camera allowed correct segmentation of the gold particles, separating them from other cell structures and from the substrate. Particle identification was performed by a classification module designed by us. Based on shape and size, the computer recognized the group of small particles and classified them as either singular or clustered and differentiated these from the single bigger type. The final image shows the particle types separated and colored, and indicates the total number of objects encountered in the specific region of interest. Moreover, a montage tool allowed us to obtain final representative images of large microscopic fields, which on analysis by the Gold Finder module provided information on the distribution and localization of antigens comparable to that provided by the wide-field light microscope images.

摘要

这项工作提出了一种计算机化方法,用于在电子显微镜(EM)中识别、检测、评估金颗粒对,并通过彩色叠加呈现,即使是在宽视野中。在配备有2k×2k像素慢扫描冷却电荷耦合器件(CCD)相机并连接到装有analySIS 3.1 PRO图像处理软件的计算机的LEO 912电子显微镜中,对双重金免疫标记的标本进行分析。相机采集的高分辨率和高动态范围图像使得金颗粒能够正确分割,将它们与其他细胞结构和底物区分开来。颗粒识别由我们设计的分类模块执行。基于形状和大小,计算机识别出小颗粒组,并将它们分类为单个或聚集的,同时将这些与单个较大类型区分开来。最终图像显示了分离并着色的颗粒类型,并指出在特定感兴趣区域中遇到的物体总数。此外,拼接工具使我们能够获得大视野微观领域的最终代表性图像,通过金颗粒查找器模块对其进行分析时,可提供与宽视野光学显微镜图像相当的抗原分布和定位信息。

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