Uylings H B, van Eden C G, Hofman M A
J Neurosci Methods. 1986 Oct;18(1-2):19-37. doi: 10.1016/0165-0270(86)90111-1.
Comparison of the different approximation equations and procedures to estimate the volume of a brain region with an irregular shape contained in parallel sections indicates that the 'basic volume estimator' using systematic section is very efficient and sufficiently accurate. Important in estimating the volume is the correction for shrinkage and the accuracy of the section thickness determination. Methods to estimate thickness of section are outlined, and the method of differential focusing is discussed. In the Appendix, the corrections are described for overestimation of the volume by overprojection of the cross-sectional area and underestimation by underprojection when the size of cross-sectional area changes non-negligibly within sections. Statistical techniques to compare bivariate linear relations of different groups are reviewed. Emphasis is laid on Model II regression techniques that are used when the two variables considered are both subject to biological variation and measurement error. A new Model II procedure is proposed to compare the coincidence of the slopes of bivariate distributions and to test whether or not an experimental bivariate sample deviates significantly from a control sample when only the control group shows a significant bivariate linear relationship.
对用于估计平行切片中包含的不规则形状脑区体积的不同近似方程和方法进行比较表明，使用系统切片的“基本体积估计器”非常有效且足够准确。估计体积时重要的是对收缩的校正以及切片厚度测定的准确性。概述了估计切片厚度的方法，并讨论了微分聚焦法。在附录中，描述了当横截面面积在切片内变化不可忽略时，由于横截面面积的过度投影导致体积高估以及由于投影不足导致低估的校正方法。回顾了比较不同组双变量线性关系的统计技术。重点介绍了模型II回归技术，当所考虑的两个变量都受到生物变异和测量误差影响时使用该技术。提出了一种新的模型II程序，用于比较双变量分布斜率的一致性，并在仅对照组显示出显著的双变量线性关系时，检验实验双变量样本是否显著偏离对照样本。
