This paper reviewed the machine learning-based studies for quantitative positron emission tomography (PET). Specifically, we summarized the recent developments of machine learning-based methods in PET attenuation correction and low-count PET reconstruction by listing and comparing the proposed methods, study designs and reported performances of the current published studies with brief discussion on representative studies. The contributions and challenges among the reviewed studies were summarized and highlighted in the discussion part followed by.

中文翻译：

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定量 PET 成像中的机器学习

本文回顾了基于机器学习的定量正电子发射断层扫描 (PET) 研究。具体来说，我们通过列出和比较当前已发表研究的拟议方法、研究设计和报告性能，并简要讨论代表性研究，总结了基于机器学习的 PET 衰减校正和低计数 PET 重建方法的最新进展。在随后的讨论部分中总结并强调了所审查研究中的贡献和挑战。