FSUE "Russian Federal Nuclear Center - Zababakhin All-Russia Research Institute of Technical Physics", Snezhinsk, Chelyabinsk Region 456770, Russia.
Phys Med. 2024 Aug;124:104491. doi: 10.1016/j.ejmp.2024.104491. Epub 2024 Jul 29.
Optimization of the dose the patient receives during scanning is an important problem in modern medical X-ray computed tomography (CT). One of the basic ways to its solution is to reduce the number of views. Compressed sensing theory helped promote the development of a new class of effective reconstruction algorithms for limited data CT. These compressed-sensing-inspired (CSI) algorithms optimize the Lp (0 ≤ p ≤ 1) norm of images and can accurately reconstruct CT tomograms from a very few views. The paper presents a review of the CSI algorithms and discusses prospects for their further use in commercial low-dose CT.
Many literature references with the CSI algorithms have been were searched. To structure the material collected the author gives a classification framework within which he describes Lp regularization methods, the basic CSI algorithms that are used most often in few-view CT, and some of their derivatives. Lots of examples are provided to illustrate the use of the CSI algorithms in few-view and low-dose CT.
A list of the CSI algorithms is compiled from the literature search. For better demonstrativeness they are summarized in a table. The inference is done that already today some of the algorithms are capable of reconstruction from 20 to 30 views with acceptable quality and dose reduction by a factor of 10.
In conclusion the author discusses how soon the CSI reconstruction algorithms can be introduced in the practice of medical diagnosis and used in commercial CT scanners.
在现代医学 X 射线计算机断层扫描（CT）中，优化患者在扫描过程中接受的剂量是一个重要问题。解决该问题的基本方法之一是减少视图数量。压缩感知理论促进了一类新的有效重建有限数据 CT 的算法的发展。这些受压缩感知启发的（CSI）算法优化了图像的 Lp（0≤p≤1）范数，可以从很少的视图准确重建 CT 断层图像。本文综述了 CSI 算法，并讨论了它们在商业低剂量 CT 中的进一步应用前景。
搜索了许多带有 CSI 算法的文献参考资料。为了对收集到的材料进行结构化，作者给出了一个分类框架，在该框架中，他描述了 Lp 正则化方法、在少视图 CT 中最常用的基本 CSI 算法以及它们的一些衍生算法。提供了大量示例来说明 CSI 算法在少视图和低剂量 CT 中的应用。
从文献检索中编译了 CSI 算法列表。为了更好地说明问题，将它们汇总在一个表格中。推断出，已经有一些算法能够以可接受的质量和 10 倍的剂量减少从 20 到 30 个视图进行重建。
最后，作者讨论了 CSI 重建算法在医疗诊断实践中引入和在商业 CT 扫描仪中使用的速度。
