Open AccessEffect of Bayesian penalty likelihood algorithm on 18F-FDG PET/CT image of lymphoma
Author(s) -
Yongtao Wang,
LiRong Lin,
Wei Quan,
Jinyu Li,
Weilong Li
Publication year - 2021
Publication title -
nuclear medicine communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.489
H-Index - 73
eISSN - 1473-5628
pISSN - 0143-3636
DOI - 10.1097/mnm.0000000000001516
Subject(s) - algorithm , lesion , lymphoma , medicine , nuclear medicine , image quality , mathematics , radiology , pathology , artificial intelligence , image (mathematics) , computer science
Recently, a new Bayesian penalty likelihood (BPL) reconstruction algorithm has been applied in PET, which is expected to provide better image resolution than the widely used ordered subset expectation maximization (OSEM). The purpose of this study is to compare the differences between these two algorithms in terms of image quality and effects on clinical diagnostics and quantification of lymphoma.