Application of the random field theory in PET imaging - injection dose optimization

Jiří Dvořák; Jiří Boldyš; Magdaléna Skopalová; Otakar Bělohlávek

Kybernetika (2013)

  • Volume: 49, Issue: 2, page 280-300
  • ISSN: 0023-5954

Abstract

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This work presents new application of the random field theory in medical imaging. Results from both integral geometry and random field theory can be used to detect locations with significantly increased radiotracer uptake in images from positron emission tomography (PET). The assumptions needed to use these results are verified on a set of real and simulated phantom images. The proposed method of detecting activation (locations with increased radiotracer concentration) is used to quantify the quality of simulated PET images. Dependence of the quality on the injection dose (amount of applied radiotracer) and patient's body parameters is estimated. It is used to derive curves of constant quality determining the injection dose needed to achieve desired quality of the resulting images. The curves are compared with the formula currently used in medical practice.

How to cite

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Dvořák, Jiří, et al. "Application of the random field theory in PET imaging - injection dose optimization." Kybernetika 49.2 (2013): 280-300. <http://eudml.org/doc/260691>.

@article{Dvořák2013,
abstract = {This work presents new application of the random field theory in medical imaging. Results from both integral geometry and random field theory can be used to detect locations with significantly increased radiotracer uptake in images from positron emission tomography (PET). The assumptions needed to use these results are verified on a set of real and simulated phantom images. The proposed method of detecting activation (locations with increased radiotracer concentration) is used to quantify the quality of simulated PET images. Dependence of the quality on the injection dose (amount of applied radiotracer) and patient's body parameters is estimated. It is used to derive curves of constant quality determining the injection dose needed to achieve desired quality of the resulting images. The curves are compared with the formula currently used in medical practice.},
author = {Dvořák, Jiří, Boldyš, Jiří, Skopalová, Magdaléna, Bělohlávek, Otakar},
journal = {Kybernetika},
keywords = {random field theory; Euler characteristic; PET imaging; PET image quality; random field theory; Euler characteristic; PET imaging; PET image quality},
language = {eng},
number = {2},
pages = {280-300},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Application of the random field theory in PET imaging - injection dose optimization},
url = {http://eudml.org/doc/260691},
volume = {49},
year = {2013},
}

TY - JOUR
AU - Dvořák, Jiří
AU - Boldyš, Jiří
AU - Skopalová, Magdaléna
AU - Bělohlávek, Otakar
TI - Application of the random field theory in PET imaging - injection dose optimization
JO - Kybernetika
PY - 2013
PB - Institute of Information Theory and Automation AS CR
VL - 49
IS - 2
SP - 280
EP - 300
AB - This work presents new application of the random field theory in medical imaging. Results from both integral geometry and random field theory can be used to detect locations with significantly increased radiotracer uptake in images from positron emission tomography (PET). The assumptions needed to use these results are verified on a set of real and simulated phantom images. The proposed method of detecting activation (locations with increased radiotracer concentration) is used to quantify the quality of simulated PET images. Dependence of the quality on the injection dose (amount of applied radiotracer) and patient's body parameters is estimated. It is used to derive curves of constant quality determining the injection dose needed to achieve desired quality of the resulting images. The curves are compared with the formula currently used in medical practice.
LA - eng
KW - random field theory; Euler characteristic; PET imaging; PET image quality; random field theory; Euler characteristic; PET imaging; PET image quality
UR - http://eudml.org/doc/260691
ER -

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