Estimating mean particle volume and number from random sections by sampling profile boundaries

Image processing and 2-D morphometry

Image analysis and image processing are becoming commonplace operations in the cytometry environment. This very practical and useful unit describes the basics of image processing, including image enhancement, feature identification, and classification and segmentation. Written by an author with strong background in electron microscopy and image analysis, the unit is well furnished with figures and examples. Anyone needing a start in doing image analysis will find this very easy and useful reading, with suitable references for those wanting to move a step further.

A new stereological principle for test lines in three-dimensional space

A new principle is presented to generate isotropic uniform random (IUR) test lines hitting a geometric structure in three-dimensional space (3D). The principle therefore concerns the estimation of surface area, volume, membrane thickness, etc., of arbitrary structures with piecewise smooth boundary. The principle states that a point-sampled test line on an isotropic plane through a fixed point in 3D is effectively an invariant test line in 3D. Particular attention is devoted to the stereology of particles, where an alternative to the surfactor method is obtained to estimate surface area. An interesting case arises when the particle is convex. The methods are illustrated with synthetic examples.

Surface-weighted star volume: concept and estimation

The estimation of 'size' for an interconnected nonconvex phase is an ongoing problem in materials science and biomedicine. Examples of this type of phase include the pore space in a porous rock such as sandstone or the marrow space found in cancellous bone. A reasonable definition of size for this type of phase is provided by the mean volume-weighted star volume. This is defined as the average volume of the phase of interest seen unobscured from a typical point within the phase. One practical advantage of this definition of size is that it is easy to estimate stereologically. In this paper we extend the concept of star volume to consider the mean surface-weighted star volume. The mean surface-weighted star volume is the volume of a continuous phase seen unobscured from a typical point of the interface. We expect that this parameter could be useful in biological problems involving mass transfer across an interface. The stereological estimation of mean surface-weighted star volume is described and the method is illustrated on piglet lung tissue.

Biological stereology: history, present state, future directions

The development of a quantitative structural platform for experimental biology--extending across a hierarchy of sizes ranging from molecules to organisms--has been punctuated by a series of major achievements over the last 30 years. Stereology, a form of quantitative morphology, has contributed handsomely to this success. A personal view is presented highlighting key events in the development of biological stereology. We also examine stereology with a view toward future developments in biology and speculate how stereology might contribute to the new biological infrastructure currently being built with computers.

Quantitative morphology for biologists and computer scientists: I. Computer-aided tutorial for biological stereology (version 1.0)

This paper describes a computer-aided tutorial for biological stereology. Stereology, a type of quantitative morphology, includes a collection of statistical methods that quantify the structural compartments that can be viewed in sections with light and electron microscopy. These methods provide volume, surface, length, shape, and number data, and help define the quantitative relationships among the structural compartments of biological hierarchies. Hierarchies, which connect structural data ranging in size from molecules to organs, serve as a central core to which the data of biological databases can be linked. The tutorial focuses on two objectives. It provides the user primarily interested in using quantitative morphology databases with background information, and offers a set of state-of-the-art tools to researchers wishing to use these methods in the laboratory. The main topics of the tutorial include: introduction to quantitative morphology, symbols/terms, data types, sampling, hierarchies, data interpretation, and utilities. The tutorial runs under the MS-DOS operating system and requires at least an IBM PC AT (or compatible), a color monitor (EGA, VGA), 540 KB of RAM, and 3 MB of hard disk space.

A review of recent advances in stereology for quantifying neural structure

The science of stereology has undergone a revolution over the past decade with the introduction of design-based (assumption- or model-free) methods which are highly efficient and generally unbiased. No other morphometric approach currently offers these twin benefits. Stereology is ideal for extrapolating 3-D structural quantities (real volumes, surface areas, lengths and numbers) from simple counts made on 2-D slice images. The images may take various forms (e.g. physical or optical sections, MRI slices, CT scans) but they must be sampled so as to be random in orientation and/or position if valid estimates are to be made. All the recent developments in stereology are applicable to problems in neuromorphometry. This review provides an account of major developments and the state of the art, emphasizes the importance of properly randomized sampling and identifies some applications to neural structure at different levels of organization. These include the counting and sizing of synapses, neurites, cells and whole brains.