1. M. Brown. PET Imaging in Oncology: Current Applications and Future Directions. Imaging Med. 16 (5) (2024) 224–225.
2. F. Hashimoto, Y. Onishi, K. Ote, H. Tashima, A. J. Reader, T. Yamaya. Deep learning-based PET image denoising and reconstruction: a review. Radiol. Phys. Technol. 17 (1) (2024) 24-46.
3. A. J. Reader, B. Pan. AI for PET image reconstruction. Br. J. Radiol. 96 (1150) (2023) 20230292.
4. M. Asemanrafat, A. Chaparian, M. Lotfi, A. Rasekhi. Impact of Iterative Reconstruction Algorithms on Image Quality and Radiation Dose in Computed Tomography Scan of Patients with Malignant Pancreatic Lesions. J. Med. Signals Sensors 12 (1) (2022) 69-75.
5. J . Llacer, E. Veklerov, K. J. Coakley, E. J. Hoffman, J. Nunez. Statistical analysis of maximum likelihood estimator images of human brain FDG PET studies. IEEE Trans. Med. Imaging. 12 (2) (1993) 215–231.
6. W. P. Segars, B. M. W. Tsui, J. Cai, F. F. Yin, G. S. Fung, E. Samei. Application of the 4D XCAT phantoms in biomedical imaging and beyond. IEEE Trans. Med. Imaging 37 (3) (2018) 680-692.
7. U. Sara, M. Akter, M. S. Uddin. Image Quality Assessment through FSIM, SSIM, MSE and PSNR: A Comparative Study. J. Comput. Commun. 7 (3) (2019) 8-18.
8. A. M. Alessio, P. E. Kinahan. PET Image Reconstruction. In: R. E. Henkin, editor. Nuclear Medicine. 2nd ed. St. Louis, MO: Mosby; 2006.
9. M. Defrise, P. E. Kinahan, C. J. Michel. Image Reconstruction Algorithms in PET. In: P. E. Valk, D. L. Bailey, D. W. Townsend, M. N. Maisey, editors. Positron Emission Tomography: Basic Sciences. Springer, London (2005) 63–91.
10. C. J. Jaskowiak, J. A. Bianco, S. B. Perlman, J. P. Fine. Influence of reconstruction iterations on 18F-FDG PET/CT standardized uptake values. J. Nucl. Med. 46 (3) (2005) 424-428.