Phantom and clinical evaluation of a new Bayesian penalized likelihood reconstruction algorithm HYPER Iterative on the image quality of 68Ga-DOTA-NOC PET/CT
Abstract:Background
Bayesian penalized likelihood (BPL) algorithm is an effective way to suppress the noise by incorporating a smooth penalty in the positron emission tomography (PET) image reconstruction process. The strength of the smooth penalty is controlled by the penalization factor. The aim was to investigate the impact of different penalization factor and acquisition time in a new BPL algorithm HYPER Iterative on the image quality of 68Ga-DOTA-NOC PET/CT. A phantom and 25 patients with neuroendocrine neoplasm … Show more
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