Normalization and scatter corrections for the J-PET scanner

A. Coussat, W. Krzemień, J. Baran, S. Parzych, L. Raczyński, N. Chug, C. Curceanu, E. Czerwiński, M. Dadgar,K. Dulski, J. Gajewski, B. Hiesmayr, K. Valsan Eliyan, A. Jędruszczak, K. Kacprzak, A. Gajos, T. Kaplanoglu, L. Kapłon, K. Klimaszewski, T. Kozik, G. Lapkiewicz, G. Korcyl, S. Moyo,D. Kumar, W. Mryka, S. Niedźwiecki,S. Sharma,E. Pérez Del Río, S. Shivani, R. Shopa, P. Tanty, M. Skurzok, K. Tayefi, F. Tayefi, E. Stępień, W. Wiślicki, P. Moskal

2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)(2023)

引用 0|浏览2
暂无评分
摘要
The Jagiellonian PET scanner is a cost-effective large axial FOV Positron Emission Tomography technology that enables multi-photon imaging and is currently under development at the Jagiellonian University. The current 50 cm prototype, named "Modular J-PET", is being investigated for various applications. It is well known that PET data can be affected by several effects during acquisition, such as scattered gamma photons or variations in detection efficiency. Consequently, achieving the reconstruction of images of satisfactory quality requires a set of corrections to be applied to each line-of-response. This summary discusses the implementation and performance of scatter and normalization corrections for the Modular J-PET, and their extension prior to the assembly of a total-body Jagiellonian PET scanner. Normalization correction is achieved using component-based normalization, a method particularly suitable for large scanners with a high number of lines-of-response. Scatter correction is achieved using an extension of the single scatter simulation technique that incorporates time-of-flight information. Reconstruction of reference phantoms based on Monte Carlo simulations highlight improvements in image quality. The application of normalization reduces the non-uniformity in the reconstructed image by a factor of 10 in the axial direction and 2 in the radial direction.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要