3 edition of Stereology and Stochastic Geometry (Computational Imaging and Vision) found in the catalog.
November 30, 2003
Written in English
|The Physical Object|
|Number of Pages||512|
An extensive update to a classic text Stochastic geometry and spatial statistics play a fundamental role in many modern branches of physics, materials sciences, engineering, biology and environmental sciences. They offer successful models for the description of random two- and three-dimensional micro and macro structures and statistical methods for their analysis. further models of stochastic geometry, namely ﬁbre processes, surface processes and ran-dom tesselations, are investigated. A large Chapter 11 is devoted to stereology, it makes use of some results of the whole previous text. This is the second edition of .
Stereology for Statisticians sets out the principles of stereology from a statistical viewpoint, focusing on both basic theory and practical implications. This book discusses ways to effectively communicate statistical issues to clients, draws attention to common methodological errors, and provides references to essential literature. Unfortunately, this book can't be printed from the OpenBook. If you need to print pages from this book, we recommend downloading it as a PDF. Visit to get more information about this book, to buy it in print, or to download it as a free PDF.
Stereology, as a branch of stochastic geometry, provides simple sampling and measurement tools to obtain unbiased estimates of quantitative parameters such as volume, number, length and surface of objects in 3D space based on measurements on almost 2D histological sections. Microscopy: 2Cited by: Stereology, Spatial Statistics, Stochastic Geometry Prague, 25 - 29 June Main topics: Plenary speakers: Application of stereology in life sciences and materials sciences Application of spatial statistics in ecology, environmental and other sciences Methodology of spatial statistics, geostatistics Stochastic geometry and random sets.
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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." Cited by: Stereology and Stochastic Geometry by John E.
Hilliard,available at Book Depository with free delivery worldwide. Get this from a library. Stereology and stochastic geometry. [John E Hilliard; Lawrence R Lawson] -- "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").
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.".
Stereology And Stochastic Geometry. Author by: John E. Hilliard Languange: en the book has been written not only for specialists in stereology, integral geometry and geometric measure theory. In particular, Chapter 1 is an elementary introduction to stereology and the book contains about 75 illustrations.
Chapter 1 is an elementary. In mathematics, stochastic geometry is the study of random spatial patterns. At the heart of the subject lies the study of random point patterns. This leads to the theory of spatial point processes, hence notions of Palm conditioning, which extend to the more abstract setting of random measures.
Stochastic geometry, geometric statistics, stereology: proceedings of a conference held at Oberwolfach, It promotes the exchange of scientific, technical, organizational and other information on the quantitative analysis of data having a geometrical structure, including stereology, differential geometry, image analysis, image processing, mathematical morphology, stochastic geometry, statistics, pattern recognition, and related topics.
A mathematical discipline in which one studies the relations between geometry and probability theory. Stochastic geometry developed from the classical integral geometry and from problems on geometric probabilities, with the introduction of ideas and methods from the theory of random processes, especially the theory of point processes.
One of the basic concepts of stochastic geometry is the. The main ideas presented have application to such areas as stereology and geometrical statistics and this book will be a useful reference book for university students studying probability theory and stochastic geometry, and research mathematicians interested in this : $ 20th Workshop on Stochastic Geometry, Stereology and Image Analysis 2–7 June,Sandbjerg Estate, Denmark Abstract book Abstracts Talks Błaszczyszyn.
The previous edition of this book has served as the key reference in its field for over 18 years and is regarded as the best treatment of the subject of stochastic geometry, both as a subject with vital applications to spatial statistics and as a very interesting field of mathematics in its own right.
Stochastic geometry, based on current developments in geometry, probability and measure theory, makes possible modeling of two- and three-dimensional random objects with interactions as they appear in the microstructure of materials, biological tissues, macroscopically in soil, geological sediments.
The workshops on stochastic geometry, stereology and image analysis have been held every second year since The ﬁrst workshops were small meetings, but with prominent speakers. Over the years, the workshops have increased in size and in impact too.
Nowadays, the workshops have developed into the main occasion toAuthor: Eva B. Vedel Jensen, Hans Jørgen G. Gundersen. “Stochastic Geometry, Geometric Statistics, Stereology” (Proceedings of the Conference held at Oberwolfach, ).
Teubner - Texte zur Mathematik, B Leipzig “Stochastic and Integral Geometry”, (Proceedings of the Second Sevan Symposium on Integral and Stochastic Geometry), in Acta Applicandae Mathematicae, Vol 9, Nos ()Born: Octo (age 78). What is stochastic geometry. Stochastic geometry is the study of random spatial patterns I Point processes I Random tessellations I Stereology Applications I Astronomy I Communications I Material science I Image analysis and stereology I Forestry I Random matrix theory GRK (IITM) Stochastic Geometry and Wireless Nets.
On the other hand, parts of stochastic geometry (random sets, point processes of convex bodies) have their roots in stereological questions. It seems, however, that stereology as an important field of applications of (convex) geometry is not as well-known to geometers as it should by: This book has a strong focus on simulations and includes extensive codes in Matlab and R which are widely used in the mathematical community.
It can be seen as a continuation of the recent volume of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered with a focus on.
The objective of stereology is to draw inferences about the geometrical properties of three dimensional structures when information is only available in lower‐dimensional form through planar sections, linear probes, or projections of thick slices.
Stereological formulae depend on some assumption of. Synopsis from The Johns Hopkins University Press. Beginning in the s, scientists across a wide range of disciplines cooperated in developing unbiased—or assumption free—stereology, based on stochastic geometry and probability theory, as a way to estimate the parameters of irregularly shaped objects without introducing bias.
3 The Notion of Stochastic Geometry In the author's opinion the relation of stochastic geometry to stereology is analogous to that of stochastic geometry to other branches of spatial statistics (such as point process statistics or statistics for random sets.) That means, stochastic geometry: (i) gives a rigorous mathematical foundation.Stereology is the science of geometric sampling, with applications to the statistical analysis of microstructures in biology and materials science.
Subsidiary disciplines are image analysis.A variety of applications of tensor valuations to models in stochastic geometry, to local stereology and to imaging are also discussed.
Keywords Minkowski tensors valuation theory convex body integral geometry stochastic geometry curvature measures valuations on manifolds normal cycle stereology.