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: Examining how PET images are formed and reconstructed is key to obtaining unique functional images. The quality of PET images has significantly improved with technological advancements. The criteria for determining a good PET image are subjective to the user, influenced by factors like reconstruction algorithms, filter choice, attenuation, and blur weighting. Sharper filters and more iterations offer higher resolution but increase noise, while smoother filters reduce noise but compromise resolution. There are pitfalls to be aware of, such as the delicate nature of algorithm tuning and the need for validation on large data samples acquired from multiple scanners with various detection tasks.
