en
Doctoral thesis
Open access
English

Strategies for improvement of PET instrumentation performance and imaging methodology

DirectorsZaidi, Habiborcid
Number of pages234
Imprimatur date2023
Defense date2023
Abstract

Achieving excellent image quality and quantitative accuracy using current generation Positron Emission Tomography (PET) scanners is mandatory for accurate clinical diagnosis and monitoring of various medical conditions. PET utilizes radioactive tracers or molecular imaging probes to produce images representing the physiology of body's internal organs and tissues, thus allowing physicians to identify and locate potential diseases and molecular pathways. The quality of the images produced by PET scanners is vital because it directly impacts the accuracy of clinical diagnosis and treatment strategies. Poor image quality can result in false positives or negatives, which in turn leads to incorrect diagnosis or ineffective treatment plans. This can ultimately compromise patient outcomes. To ensure high-quality images, PET scanners must have a high spatial resolution and sensitivity. Spatial resolution refers to the ability of the scanner to distinguish between two closely located objects, whereas the sensitivity refers to its ability to detect small amounts of the radioactive tracer. PET scanners with high image quality can detect even small changes in the body's metabolism and physiological functions, which can be indicative of early-stage disease. This early detection can lead to earlier intervention and more successful treatment outcomes. In summary, image quality is of utmost importance in PET imaging as it directly affects the accuracy of diagnosis and treatment outcomes.

This dissertation and portfolio of published works presented here aim to showcase various approaches and strategies devised to enhance PET scanning procedures in terms of convenience, safety, and accuracy. These improvements are achieved through both hardware (instrumentation) and software (imaging methodology) enhancements.

eng
Keywords
  • Artificial Intelligence
  • Medical Imaging
  • PET
  • CT
  • MRI
  • Radiology
  • Low dose PET
  • Monte Carlo Simulation
  • GATE
  • Instrumentation
Citation (ISO format)
SANAAT, Amirhossein. Strategies for improvement of PET instrumentation performance and imaging methodology. 2023. doi: 10.13097/archive-ouverte/unige:171571
Main files (1)
Thesis
accessLevelPublic
Secondary files (1)
Identifiers
101views
277downloads

Technical informations

Creation09/20/2023 12:07:46 PM
First validation09/21/2023 2:06:48 PM
Update time09/21/2023 2:06:48 PM
Status update09/21/2023 2:06:48 PM
Last indexation05/06/2024 5:01:11 PM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack