Statistical modeling for data of positron emission tomography in depression

Document Type

Syllabus

Publication Date

1-1-2011

Abstract

ne of the main applications of Positron Emission Tomography (PET) is to estimate the density of a neuroreceptor at each location throughout the brain by measuring the concentration of a radiotracer over time and modeling its kinetics. Several statistical approaches to modeling the kinetics have been proposed in the literature. In this article, we will first briefly review the PET imaging acquisition process and then focus on reviewing several kinetic models for PET data, including compartment models, graphical models, and Basis Pursuit. We will also briefly discuss how to model the plasma function (input function) and how to use metabolites to correct the input function.

Identifier

85116540787 (Scopus)

ISBN

[9789814329804]

Publication Title

Recent Advances in Biostatistics False Discovery Rates Survival Analysis and Related Topics

External Full Text Location

https://doi.org/10.1142/9789814329804_0013

First Page

247

Last Page

256

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