Chapter 13. Application of Multivariate Image Analysis in Nuclear Medicine: Principal Component Analysis (PCA) on Dynamic Human Brain Studies with Positron Emission Tomography (PET) for Discrimination of Areas of Disease at High Noise Levels

  1. Hans F. Grahn3 and
  2. Paul Geladi4
  1. Pasha Razifar1 and
  2. Mats Bergström2

Published Online: 19 NOV 2007

DOI: 10.1002/9780470010884.ch13

Techniques and Applications of Hyperspectral Image Analysis

Techniques and Applications of Hyperspectral Image Analysis

How to Cite

Razifar, P. and Bergström, M. (2007) Application of Multivariate Image Analysis in Nuclear Medicine: Principal Component Analysis (PCA) on Dynamic Human Brain Studies with Positron Emission Tomography (PET) for Discrimination of Areas of Disease at High Noise Levels, in Techniques and Applications of Hyperspectral Image Analysis (eds H. F. Grahn and P. Geladi), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470010884.ch13

Editor Information

  1. 3

    Division of Behavioral Neuroscience, Department of Neuroscience, Karolinska Institutet, S-17177, Stockholm, Sweden

  2. 4

    NIRCE, The Unit of Biomass Technology and Chemistry SLU Röbäcksdalen, PO Box 4097, SE 90403 Umeå, Sweden

Author Information

  1. 1

    Computerized Image Analysis & PET Uppsala Applied Science Lab (UASL) GEMS PET Systems AB, Husbyborg, 752 28 Uppsala, Sweden

  2. 2

    Novartis Pharma AG, CH-4002, Basel, Switzerland

Publication History

  1. Published Online: 19 NOV 2007
  2. Published Print: 27 SEP 2007

ISBN Information

Print ISBN: 9780470010860

Online ISBN: 9780470010884

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Keywords:

  • Positron emission tomography (PET);
  • variance-covariance structures;
  • data-driven technique;
  • annihilation coincidence detection (ACD);
  • positron emission transaxial tomography (PETT);
  • filtered back projection (FBP);
  • ordered subset expectation maximization (OSEM);
  • kinetic modellingmethods;
  • analysis and visualization of anatomy and pathology;
  • singular value decomposition (SVD)

Summary

This chapter contains sections titled:

  • Introduction

  • PET

  • PCA

  • Application of PCA in PET

  • Conclusions

  • References