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Nükleer görüntülemede parsiyel hacim etkisi(PVE) düzeltmesi: özel fantom geliştiri̇lmesive kli̇ni̇k cihazlarda doğrulanmasi

2024
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Advisor: Prof. Dr. Cengizhan Öztürk

Abstract (EN)

Positron Emission Tomography (PET) imaging is a powerful and widely utilized modality in the field of Nuclear Medicine, particularly for the diagnosis and monitoring of cancer. This project aims to design and produce a unique anthropomorphic PET phantom that mimics human tissue properties; Utilize the developed phantom to calculate corrected Standard Uptake Values (SUVs) for oncological lesions by applying Recovery Coefficients (RCs) determined for Partial Volume Effect (PVE) correction. SUV is a widely utilized quantitative parameter in PET imaging, representing the concentration of radiotracer uptake within a region of interest (ROI) relative to its overall distribution in the body. However, the accuracy of SUV measurements can be compromised by the PVE, a phenomenon that arises when the spatial resolution of the imaging system is insufficient to clearly distinguish between adjacent tissues or structures within a single voxel, leading to underestimation or overestimation of radiotracer concentration. This dissertation is dedicated to exploring the critical area of PVE correction in F18-FDG PET imaging, focusing on the use of anthropomorphic phantoms as a fundamental platform for in-depth studies. By simulating anatomical conditions representative of the human body, anthropomorphic phantoms serve as important test phantoms for the evaluation of correction algorithms and provide insights into their efficacy and limitations. Through methodical experimentation and careful analysis, the research described here aims to make a significant contribution towards the refinement of PVE correction strategies, to increase the accuracy and reliability of F18- FDG PET imaging in the future.

Author

Dr. Güneş Yavuz

How to Cite

Güneş Yavuz (Doctorate thesis). Nükleer görüntülemede parsiyel hacim etkisi(PVE) düzeltmesi: özel fantom geliştiri̇lmesive kli̇ni̇k cihazlarda doğrulanmasi, 2024, Boğaziçi University.

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