Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- Nomenclature
- 1 Overview of biomedical image analysis
- Part I Signals and systems, image formation, and image modality
- Part II Stochastic models
- 4 Random variables
- 5 Random processes
- 6 Basics of random fields
- 7 Probability density estimation by linear models
- Part III Computational geometry
- Part IV Variational approaches and level sets
- Part V Image analysis tools
- Index
- References
5 - Random processes
from Part II - Stochastic models
Published online by Cambridge University Press: 05 November 2014
Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- Nomenclature
- 1 Overview of biomedical image analysis
- Part I Signals and systems, image formation, and image modality
- Part II Stochastic models
- 4 Random variables
- 5 Random processes
- 6 Basics of random fields
- 7 Probability density estimation by linear models
- Part III Computational geometry
- Part IV Variational approaches and level sets
- Part V Image analysis tools
- Index
- References
Summary
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- Type
- Chapter
- Information
- Biomedical Image AnalysisStatistical and Variational Methods, pp. 107 - 130Publisher: Cambridge University PressPrint publication year: 2014
References
, Probability, Random Variables and Stochastic Processes, 3rd Edition. New York: McGraw-Hill (1991).Google Scholar
, Grundbegriffe der Wahrscheinlichkeitsrechnung (in German). Berlin: Julius Springer. Translation: A. Kolmogorov, Foundations of the Theory of Probability, 2nd Edition. New York: Chelsea (1956).Google Scholar