ISS was a well established international scientific society aiming to promote stereology and image analysis in a wide range of disciplines with members from many different fields of science such as mathematics, biomedicine, computer science, material science, statistics, geology, stochastic geometry, etc.
In 2016 the society expanded its scope to the whole field of image analysis and renamed to International Society for Stereology & Image Analysis.
Is this the first time you stumble on the word stereology?
From its greek roots "stereo"and"logos" the term means the "science of studying solids".
In practice, it was originally defined in modern science as "the spatial interpretation of sections". It is an interdisciplinary field that is largely concerned with the three-dimensional interpretation of planar sections of materials or tissues. It provides practical techniques for extracting quantitative information about a three-dimensional material from measurements made on two-dimensional planar sections of the material.
Stereology is a method that utilizes random, systematic sampling to provide unbiased and quantitative data. It is an important and efficient tool in many applications of microscopy (such as petrography, materials science, and biosciences including histology, bone and neuroanatomy). Stereology is a developing science with many important innovations being developed mainly in Europe. New innovations such as the proportionator continue to make important improvements in the efficiency of stereological procedures.
In addition to two-dimensional plane sections, stereology also applies to three-dimensional slabs (e.g. 3D microscope images), one-dimensional probes (e.g. needle biopsy), projected images, and other kinds of 'sampling'. It is especially useful when the sample has a lower spatial dimension than the original material. Hence, stereology is often defined as the science of estimating higher dimensional information from lower dimensional samples.
Stereology is based on fundamental principles of geometry (e.g. Cavalieri's principle) and statistics (mainly survey sampling inference). It is a completely different approach from computed tomography.
(c) Adrian Baddeley
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