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Erschienen in:
Object Segmentation and Markov Random Fields Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

Statistical Atlases

verfasst von : C. Davatzikos, R. Verma, D. Shen

Erschienen in: Handbook of Biomedical Imaging

Verlag: Springer US

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Abstract

This chapter discusses the general concept of statistical atlases built from medical images. A statistical atlas is a quantitative reflection of normal variability in anatomy, function, pathology, or other imaging measurements, and it allows us to establish a baseline against which abnormal images are to be compared for diagnostic or treatment planning purposes. Constructing a statistical atlas relies on a fundamental building block, namely deformable registration, which maps imaging data from many individuals to a common coordinate system, so that statistics of normal variability, as well as abnormal deviations from it, can be performed. 3D and 4D registration methods are discussed. This chapter also discusses the statistical analyses applied to co-registered normative images, and finally briefly touches upon use of machine learning for detection of imaging patterns that distinctly deviate from the normative range to allow for individualized classification.

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Vorheriges Kapitel Active Shape and Appearance Models
Nächstes Kapitel Statistical Computing on Non-Linear Spaces for Computational Anatomy
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Metadaten
Titel
Statistical Atlases
verfasst von
C. Davatzikos
R. Verma
D. Shen
Copyright-Jahr
2015
Verlag
Springer US
Buch
Handbook of Biomedical Imaging

Print ISBN: 978-0-387-09748-0

Electronic ISBN: 978-0-387-09749-7

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-0-387-09749-7_7

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