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体视学中的测量误差与抽样变异:平面图像分析中各种方法的效率比较

Measuring error and sampling variation in stereology: comparison of the efficiency of various methods for planar image analysis.

作者信息

Mathieu O, Cruz-Orive L M, Hoppeler H, Weibel E R

出版信息

J Microsc. 1981 Jan;121(Pt 1):75-88. doi: 10.1111/j.1365-2818.1981.tb01200.x.

Abstract

An evaluation is made of the relative efficiency (precision of the final estimate per unit time of measurement on a given set of sections) of different methods for planar analysis aimed at estimating aggregate, overall stereological parameters (such as VV, SV). The methods tested are point-counting with different densities of test points (4 less than or equal to PT less than 900 per picture), semiautomatic computer image analysis with MOP and automatic image analysis with Quantimet, for obtaining VV and SV estimates. One biological sample as well as three synthetic model structures with known coefficients of variation between sections are used. The standard error of an estimate is mainly determined by the coefficient of variation between sampling units (= sections in the present paper) so that measuring each sample unit with a very high precision is not necessary. Automatic image analysis and point-counting with a 100-point grid were the most efficient methods for reducing the relative standard errors of the VV and SV estimates to equivalent levels in the synthetic models. Using a 64-point grid was as precise, and about 11 times faster than using a tracing device for obtaining the estimate of VV in the biological sample.

摘要

针对旨在估计总体立体学参数(如体积分数(VV)、表面积密度(SV))的不同平面分析方法,对其相对效率(在给定的一组切片上每单位测量时间的最终估计精度)进行了评估。所测试的方法包括使用不同测试点密度(每张图片4≤PT≤900)的点计数法、使用MOP的半自动计算机图像分析以及使用Quantimet的自动图像分析,以获得VV和SV估计值。使用了一个生物样本以及三个在切片之间具有已知变异系数的合成模型结构。估计值的标准误差主要由采样单元(=本文中的切片)之间的变异系数决定,因此无需以非常高的精度测量每个样本单元。在合成模型中,自动图像分析和使用100点网格的点计数法是将VV和SV估计值的相对标准误差降低到同等水平的最有效方法。在生物样本中,使用64点网格与使用追踪装置获得VV估计值的精度相同,且速度快约11倍。

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