Unbiased Stereology, Second Edition is a practical guide to making unbiased 3-D measurements via the microscope. Only those stereological techniques which have been tried and tested by real application are included. Although this technology is essentially mathematical and statistical, the authors do not immerse the reader in complex analysis, but rather provide simple heuristic explanations and references to the original proof, and illustrate the theory by analogies drawn from everyday experience. To give practical experience in application of the techniques, exercises are provided at the end of each chapter, complete with detailed worked answers.

vi on geometric probability is included, students can be expected to create a few simple programs like those shown, but for other geometries. I am indebted to Tom Hare for critical reviews of the material and an endless enthusiasm to debate and derive stereological relationships; to John Matzka at Plenum Press for patiently instructing me in the intricacies of typesetting; to Chris Russ for helping to program many of these measurement techniques; and especially to Helen Adams, both for her patience with my creative fever to write yet another book, and for pointing out that the title, which I had intended to contrast to "theoretical stereology," can also be understood as the antonym of "impractical stereology." John C. Russ Raleigh,NC July, 1986 Chapter 1: Statistics 1 Accuracy and precision 1 The mean and standard deviation 5 Distributions 7 Comparison 13 Correlation 18 Nonlinear fitting 19 Chapter 2: Image Types 23 Planar sections 23 Projected images 25 Finite sections 28 Space-filling structures and dispersed phases 29 Types of images and contrast mechanisms 31 Sampling 32 Chapter 3: Manual Methods 35 Volume fraction 35 Surface density 38 Contiguity 41 Mean intercept length 42 Line density 43 Grain size determination 55 Curvature 48 Reticles to aid counting 49 Magnification and units 51 Chapter4: Size Distributions 53 Intercept length in spheres 53 Nonspherical shapes 57 Corrections for finite section thickness 59 Lamellae 61 Measurement of profile size 62 Nonspherical particles 69 vii Contents viii Chapter 5: Computer Metlwds 73

Setting out the principles of stereology from a statistical viewpoint, this book focuses on both basic theory and practical implications. The authors discuss ways to effectively communicate statistical issues to clients, draw attention to common methodological errors, and provide references to essential literature. The first full text on design-based stereology opens with a review of classical and modern stereology, followed by a treatment of mathematical foundations and then on to core techniques. The final chapters discuss implementing techniques in practical sampling designs, summarize understanding of the variance of stereological estimators, and describe open problems for further research. The book also details isotropic, vertical or local sampling designs for estimating stereological parameters such as volume, surface area, particle number and spatial distribution. This extensive text offers support to statistical consultants using examples, applications and unique Advice to Consultants sections. It contains numerous literature references, bibliographic notes and nearly 150 illustrations.

"An important book for the libraries of professionals in neurobiology, neurology, and neurosurgery." -- Doody's Book Review Service

Stereology is a valuable tool for neuroscientists, allowing them to obtain 3-Dimensional information from 2-Dimensional measurements made on appropriately sampled sections (usually obtained from histological sections or MRI/CT/PET scans). This 3-D information is invaluable in correlatingstructural/functional relationships in the pursuit of far greater understanding of the function of the central nervous system. However, in carrying out such measurements, often based on limited data sets, there is a risk of experimenter bias. An important feature of modern design based stereology isto be aware of potential sources of bias and eliminate them during the data collection. With many of the major neuroscience journals now insisting that quantitative data be presented, there is a greater need than ever for neuroscientists to understand the theory and practice behind quantitativemethods, such as those offered by stereology. Quantitative Methods in Neuroscience is a cookbook of stereological methods written especially for neuroscientists. It provides clear and accessible advice about when and when not to use stereology. Throughout the book, the emphasis is on practical guidance, rather than discussions and formulae.Written by leading scientists in the field of stereology, with a Foreword by D.C. Sterio, the book will be a valuable introduction to these methods for neuroscientists, and all those involved in development of new drug programmes.

This update to Peter R. Mouton’s pioneering work provides bioscientists with the concepts needed in order to apply the principles and practices of unbiased stereology to research involving biological tissues. Mouton starts with a brief explanation of the history and theory of the process before defining the terms, concepts, and tools of unbiased stereological procedures. He compares and contrasts the procedures with less-exacting approaches to quantitative analysis of biological structure using specific examples from biomedical literature. The book incorporates existing best practices with new methodologies, such as the Rare Event Protocol, while simplifying the dense, often difficult literature on the subject to show the utility and importance of unbiased stereology. This clear, insightful guide goes a step further than other books on this subject by demonstrating not only how to use unbiased stereology but also how to interpret and present the results. Written by the official U.S. representative to the International Society for Stereology, this is the most complete, up-to-date resource on the science of unbiased stereology. Those new to bioscience research as well as experienced practitioners will find that Mouton’s explanations are the perfect companion for stereology courses and workshops.

During recent years, people involved in developing new metals and materials for use in some of the rather extreme conditions of stress, temperature, and environment have relied heavily on the microstructural condition of their materials. In fact, many of the newer materials, such as dispersion-strengthened alloys, have been designed almost entirely by first determining the microstruc ture desired and then finding the right combination of composition, heat treatment, and mechanical working that will result in the de sired microstructure. Furthermore, the extremely high reliability required of materials used today, for example, in aerospace and nuclear energy systems, requires close control on the microstruc tural conditions of materials. This is clearly evident from even a cursory examination of recently written specifications for mate rials where rather precise microstructural parameters are stipu lated. Whereas specifications written several years ago may have included microstructural requirements for details such as ASTM grain size or graphite type, today's specifications are beginning to include such things as volume fraction of phases, mean free path of particles, and grain intercept distances. Rather arbitrary terms such as "medium pearlite" have been replaced by requirements such as "interlamella spacing not to exceed 0. 1 micron. " Finally, materials users have become increasingly aware that when a material does fail, the reason for its failure may be found by examining and "reading" its microstructure. The responsibility for a particular microstructure and a resulting failure is a matter of growing importance in current product liability consider ations.