@phdthesis{8662366,
  abstract     = {In this PhD dissertation, we propose to evaluate the impact of using different PET isotopes for
the National Electrical Manufacturers Association (NEMA) tests performance evaluation of the
GE Signa integrated PET/MR. The methods were divided into three closely related categories:
NEMA performance measurements, system modelling and evaluation of the image quality of
the state-of-the-art of clinical PET scanners. NEMA performance measurements for
characterizing spatial resolution, sensitivity, image quality, the accuracy of attenuation and
scatter corrections, and noise equivalent count rate (NECR) were performed using clinically
relevant and commercially available radioisotopes. Then we modelled the GE Signa integrated
PET/MR system using a realistic GATE Monte Carlo simulation and validated it with the result of
the NEMA measurements (sensitivity and NECR). Next, the effect of the 3T MR field on the
positron range was evaluated for F-18, C-11, O-15, N-13, Ga-68 and Rb-82. Finally, to evaluate the image
quality of the state-of-the-art clinical PET scanners, a noise reduction study was performed
using a Bayesian Penalized-Likelihood reconstruction algorithm on a time-of-flight PET/CT
scanner to investigate whether and to what extent noise can be reduced. The outcome of this
thesis will allow clinicians to reduce the PET dose which is especially relevant for young
patients. Besides, the Monte Carlo simulation platform for PET/MR developed for this thesis will
allow physicists and engineers to better understand and design integrated PET/MR systems.},
  author       = {De Vasconcelos Caribé, Paulo Rauli Rafeson},
  isbn         = {9789463553667},
  keywords     = {PET-CT,PET-MR,MonteCarlo,SystemModelling},
  language     = {eng},
  pages        = {xx,158},
  publisher    = {Universiteit Gent. Faculteit Ingenieurswetenschappen en Architectuur},
  school       = {Ghent University},
  title        = {Evaluation of image quality and reconstruction parameters in recent PET-CT and PET-MR systems},
  year         = {2020},
}