论文标题
定量宠物成像中的机器学习
Machine Learning in Quantitative PET Imaging
论文作者
论文摘要
本文回顾了基于机器学习的定量正电子发射断层扫描（PET）的研究。具体而言，我们总结了基于机器学习的方法在宠物衰减校正中基于机器学习的方法的最新发展，并通过列出并比较了所提出的方法，研究设计和报道的当前已发表研究的表现以及对代表性研究的简要讨论。审查研究中的贡献和挑战在讨论部分中得到了总结和强调。
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.
