Bias in image analysis and its solution: unbiased stereology

Abstract

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.