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Modelling random coincidences in positron emission tomography by using singles and prompts: A comparison study

Josep F. Oliver, M. Rafecas

Abstract

Random coincidences degrade the image in Positron Emission Tomography, PET. To compensate for their degradation effects, the rate of random coincidences should be estimated. Under certain circumstances, current estimation methods fail to provide accurate results. We propose a novel method, "Singles-Prompts" (SP), that includes the information conveyed by prompt coincidences and models the pile-up. The SP method has the same structure than the well-known "Singles Rate" (SR) approach. Hence, SP can straightforwardly replace SR. In this work, the SP method has been extensively assessed and compared to two conventional methods, SR and the delayed window (DW) method, in a preclinical PET scenario using Monte-Carlo simulations. SP offers accurate estimates for the randoms rates, while SR and DW tend to overestimate the rates (∼10%, and 5%, respectively). With pile-up, the SP method is more robust than SR (but less than DW). At the image level, the contrast is overestimated in SR-corrected images, +16%, while SP produces the correct value. Spill-over is slightly reduced using SP instead of SR. The DW images values are similar to those of SP except for low-statistic scenarios, where DW behaves as if randoms were not compensated for. In particular, the contrast is reduced, -16%. In general, the better estimations of SP translate into better image quality.

OriginalspracheEnglisch
Aufsatznummere0162096
ZeitschriftPLoS ONE
Jahrgang11
Ausgabenummer9
ISSN1553-7390
DOIs
PublikationsstatusVeröffentlicht - 01.09.2016

Fördermittel

This work was supported by the Spanish Ministry of Science and Innovation under grant FPA2010-14891 and the Generalitat Valenciana under grant GVISIC/2012/020. The work was also supported by Universit?t zu L?beck. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

  1. SDG 3 – Gesundheit und Wohlergehen
    SDG 3 – Gesundheit und Wohlergehen
  2. SDG 9 – Industrie, Innovation und Infrastruktur
    SDG 9 – Industrie, Innovation und Infrastruktur

Strategische Forschungsbereiche und Zentren

  • Forschungsschwerpunkt: Biomedizintechnik

DFG-Fachsystematik

  • 2.22-32 Medizinische Physik, Biomedizinische Technik

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