Article: Evaluation of a Bayesian penalized likelihood reconstruction algorithm for low-count clinical
2019 Volume 6, Issue 1, Page(s) 32
Abstract: Background: Recently, a Bayesian penalized likelihood (BPL) reconstruction algorithm was introduced for a commercial PET/CT with the potential to improve image quality. We compared the performance of this BPL algorithm with conventional reconstruction ... ...
Abstract | Background: Recently, a Bayesian penalized likelihood (BPL) reconstruction algorithm was introduced for a commercial PET/CT with the potential to improve image quality. We compared the performance of this BPL algorithm with conventional reconstruction algorithms under realistic clinical conditions such as daily practiced at many European sites, i.e. low Results: To study the performance of the BPL algorithm, regular clinical Conclusions: The BPL algorithm performs better than the standard OSEM+PSF algorithm on small lesion detectability, SUV recovery, and noise suppression. Increase of the percentage of bed overlap, time per BP, administered activity, or the β-value, all have a direct positive impact on image quality, though the latter with some loss of small lesion detectability. Thus, BPL algorithms are very interesting for improving image quality, especially in small lesion detectability. |
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Language | English |
Publishing date | 2019-12-30 |
Publishing country | Germany |
Document type | Journal Article |
ZDB-ID | 2768912-8 |
ISSN | 2197-7364 |
ISSN | 2197-7364 |
DOI | 10.1186/s40658-019-0262-y |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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