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Noise reduction using a Bayesian penalized-likelihood reconstruction algorithm on a time-of-flight PET-CT scanner
PURPOSE: Q.Clear is a block sequential regularized expectation maximization (BSREM) penalized-likelihood reconstruction algorithm for PET. It tries to improve image quality by controlling noise amplification during image reconstruction. In this study, the noise properties of this BSREM were compared...
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| 出版年: | EJNMMI Phys |
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| 主要な著者: | , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Springer International Publishing
2019
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6904688/ https://ncbi.nlm.nih.gov/pubmed/31823084 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s40658-019-0264-9 |
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