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Bias in image analysis and its solution: unbiased stereology

机译:图像分析中的偏差及其解决方案:无偏立体

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摘要

Although the human eye is excellent for pattern recognition, it often lacks the sensitivity to detect subtle changes in particle density. Because of this, quantitative evaluation may be required in some studies. A common type of quantitative assessment used for routine toxicology studies is two-dimensional histomorphometry. Although this technique can provide additional information about the tissue section being examined, it does not give information about the tissue as a whole. Furthermore, it produces biased (inaccurate) data that does not take into account the size, shape, or orientation of particles. In contrast, stereology is a technique that utilizes stringent sampling methods to obtain three-dimensional information about the entire tissue that is unbiased. The purpose of this review is to illuminate the sources of bias with two-dimensional morphometry, how it can affect the data, and how that bias is minimized with stereology.
机译:尽管人眼在模式识别方面非常出色,但它通常缺乏检测微粒密度细微变化的灵敏度。因此,在某些研究中可能需要定量评估。用于常规毒理学研究的定量评估的一种常见类型是二维组织形态计量学。尽管此技术可以提供有关正在检查的组织切片的其他信息,但它不能提供有关整个组织的信息。此外,它会产生未考虑颗粒的大小,形状或方向的偏差(不准确)数据。相反,立体学是一种利用严格的采样方法来获得有关整个组织无偏的三维信息的技术。这篇综述的目的是通过二维形态学来阐明偏差的来源,它如何影响数据以及如何通过立体学将偏差最小化。

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