Hutton B F, Hudson H M, Beekman F J
Department of Medical Physics and Department of Nuclear Medicine and Ultrasound, Westmead Hospital, Sydney, Australia.
Eur J Nucl Med. 1997 Jul;24(7):797-808. doi: 10.1007/BF00879671.
Although the potential benefits of maximum likelihood reconstruction have been recognised for many years, the technique has only recently found widespread popularity in clinical practice. Factors which have contributed to the wider acceptance include improved models for the emission process, better understanding of the properties of the algorithm and, not least, the practicality of application with the development of acceleration schemes and the improved speed of computers. The objective in this article is to present a framework for applying maximum likelihood reconstruction for a wide range of clinically based problems. The article draws particularly on the experience of the three authors in applying an acceleration scheme involving use of ordered subsets to a range of applications. The potential advantages of statistical reconstruction techniques include: (a) the ability to better model the emission and detection process, in order to make the reconstruction converge to a quantitative image, (b) the inclusion of a statistical noise model which results in better noise characteristics, and (c) the possibility to incorporate prior knowledge about the distribution being imaged. The great flexibility in adapting the reconstruction for a specific model results in these techniques having wide applicability to problems in clinical nuclear medicine.
尽管最大似然重建的潜在优势已被认可多年，但该技术直到最近才在临床实践中广泛流行。促成其更广泛接受的因素包括：改进的发射过程模型、对算法特性的更好理解，以及随着加速方案的发展和计算机速度的提高，应用的实用性。本文的目的是为将最大似然重建应用于广泛的临床问题提供一个框架。本文特别借鉴了三位作者在将涉及使用有序子集的加速方案应用于一系列应用中的经验。统计重建技术的潜在优势包括：(a) 能够更好地对发射和检测过程进行建模，以使重建收敛到定量图像；(b) 包含统计噪声模型，从而具有更好的噪声特性；(c) 有可能纳入关于被成像分布的先验知识。针对特定模型调整重建的极大灵活性使得这些技术在临床核医学问题中具有广泛的适用性。
