Springer Stereology and Stochastic Geometry: 28 (Computational Imaging and Vision, 28)

This book, written for the scientist-practitioner, presents in a concise, understandable, step-by-step form, the derivations of all the formulas of classical stereology ("quantitative microscopy") along with those of such modern constructs as star volume and the disector. Striving for simplicity, it is an attack on obfuscation by one of the founders of the field of stereology. Anatomists, histologists, materials scientists and geo-scientists will find this work an extremely readable explanation of the theory underlying their procedures. It covers the formulas for methods based on sectioning as well as those based on plane projections as used in transmission electron microscopy and point projections as used in photogrammetry. It reintroduces the useful Cahn-Hilliard estimators for the variances of stereological measurements, originally published by the National Bureau of Standards. Review From the reviews: "Mathematical stereology aims to make inference about the properties of random sets in Euclidean space using numerical characteristics of their lower-dimensional sections or projections. The main tools are based on application of methods from stochastic geometry (in particular point processes), convex geometry and geometric measure theory. … The book under review aims to provide an introduction to stereology for non-mathematicians." (Ilya S. Molchanov, Zentralblatt MATH, Vol. 1108 (10), 2007)