Department of Cardiovascular CT, Royal Brompton Hospital, London, UK.
Joint Department of Physics, The Royal Marsden, London, UK.
J Cardiovasc Comput Tomogr. 2020 May-Jun;14(3):219-225. doi: 10.1016/j.jcct.2019.04.008. Epub 2019 Apr 16.
Image reconstruction is an increasingly complex field in CT. Iterative Reconstruction (IR) is at present an adjunct to standard Filtered Back Projection (FBP) reconstruction, but could become a replacement for it. Due to its potential for scanning at lower radiation doses, IR has received a lot of attention in the medical literature and all vendors offer commercial solutions. Its use in cardiovascular CT has been driven in part due to concerns about radiation dose and image quality. This paper is the first manuscript of a pair. It aims to review the basic principles of CT scanning, to describe image reconstruction using Filtered Back Projection, and to identify the physical processes that contribute to image noise which IR may be able to compensate for. The aim is to enable cardiovascular imagers to understand what happens to the raw data prior to the reconstruction process so they may have a better appreciation of the strengths and weaknesses of the various reconstruction techniques available. The second manuscript of this pair will discuss the various vendor permutations of IR in more detail, including the most recent machine learning based offerings, and critically appraise the current clinical research available on the various IR techniques used in cardiovascular CT.
图像重建是 CT 中一个日益复杂的领域。迭代重建（IR）目前是标准滤波反投影（FBP）重建的辅助手段，但可能会取代它。由于其在较低辐射剂量下进行扫描的潜力，IR 在医学文献中受到了广泛关注，所有供应商都提供商业解决方案。它在心血管 CT 中的应用部分是由于对辐射剂量和图像质量的担忧。本文是一对论文中的第一篇。它旨在回顾 CT 扫描的基本原理，描述使用滤波反投影进行图像重建，并确定可能有助于补偿 IR 图像噪声的物理过程。目的是使心血管成像师能够了解重建过程之前原始数据的变化情况，以便他们更好地了解各种可用重建技术的优缺点。这对论文中的第二篇将更详细地讨论各种供应商的 IR 排列，包括最新的基于机器学习的产品，并批判性地评估当前可用于心血管 CT 中各种 IR 技术的临床研究。
