Abstract The combination of positron emission tomography (PET) with magnetic resonance (MR) imaging opens the way to more accurate diagnosis and improved patient management. At present, the data acquired by PET-MR scanners are essentially processed separately, but the opportunity to improve accuracy of the tomographic reconstruction via synergy of the two imaging techniques is an active area of research. In this paper, we present Release 2.1.0 of the CCP-PETMR Synergistic Image Reconstruction Framework (SIRF) software suite, providing an open-source software platform for efficient implementation and validation of novel reconstruction algorithms. SIRF provides user-friendly Python and MATLAB interfaces built on top of C++ libraries. SIRF uses advanced PET and MR reconstruction software packages and tools. Currently, for PET this is Software for Tomographic Image Reconstruction (STIR); for MR, Gadgetron and ISMRMRD; and for image registration tools, NiftyReg. The software aims to be capable of reconstructing images from acquired scanner data, whilst being simple enough to be used for educational purposes. The most recent version of the software can be downloaded from http://www.ccppetmr.ac.uk/downloads and https://github.com/CCPPETMR/ . Program summary Program Title: Synergistic Image Reconstruction Framework (SIRF) Program Files DOI: http://dx.doi.org/10.17632/s45f5jh55j.1 Licensing provisions: GPLv3 and Apache-2.0 Programming languages: C++, C, Python, MATLAB Nature of problem: In current practice, data acquired by PET-MR scanners are processed separately. Methods for improving the accuracy of the tomographic reconstruction using the synergy of the two imaging techniques are actively being investigated by the PET-MR research and development community, however, practical application is heavily reliant on software. Open-source software available to the PET-MR community – such as the PET package (STIR) (Thielemans et al., 2012) and the MR package Gadgetron (Hansen and Sorensen, 2013) – provide a basis for new synergistic PET-MR software. However, these two software packages are independent and have very different software architectures. They are mostly written in C++ but many researchers in the PET-MR community are more familiar with script-style languages, such as Python and MATLAB, which enable rapid prototyping of novel reconstruction algorithms. In the current situation it is difficult for researchers to exploit any synergy between PET and MR data. Furthermore, techniques from one field cannot easily be applied in the other. Solution method: In SIRF, the bulk of computation is performed by available advanced open-source reconstruction and registration software (currently STIR, Gadgetron and NiftyReg) that can use multithreading and GPUs. The SIRF C++ code provides a thin layer on top of these existing libraries. The SIRF layer has unified data-containers and access mechanisms. This C++ layer provides the basis for a simple and intuitive Python and MATLAB interface, enabling users to quickly develop and test their reconstruction algorithms using these scripting languages only. At the same time, advanced users proficient in C++ can directly utilise wider SIRF functionality via the SIRF C++ libraries that we provide.

中文翻译：

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SIRF：协同图像重建框架

摘要 正电子发射断层扫描 (PET) 与磁共振 (MR) 成像的结合为更准确的诊断和改进的患者管理开辟了道路。目前，PET-MR 扫描仪获取的数据基本上是单独处理的，但是通过两种成像技术的协同来提高断层扫描重建精度的机会是一个活跃的研究领域。在本文中，我们介绍了 CCP-PETMR 协同图像重建框架 (SIRF) 软件套件的 2.1.0 版，为有效实现和验证新型重建算法提供了一个开源软件平台。SIRF 提供建立在 C++ 库之上的用户友好的 Python 和 MATLAB 接口。SIRF 使用先进的 PET 和 MR 重建软件包和工具。现在，对于 PET，这是用于断层图像重建 (STIR) 的软件；适用于 MR、Gadgetron 和 ISMRMRD；对于图像注册工具，NiftyReg。该软件旨在能够从获取的扫描仪数据中重建图像，同时足够简单以用于教育目的。该软件的最新版本可以从 http://www.ccppetmr.ac.uk/downloads 和 https://github.com/CCPPETMR/ 下载。程序摘要 程序名称：协同图像重建框架 (SIRF) 程序文件 DOI：http://dx.doi.org/10.17632/s45f5jh55j.1 许可条款：GPLv3 和 Apache-2.0 编程语言：C++、C、Python、MATLAB Nature问题所在：在目前的实践中，PET-MR 扫描仪采集的数据是分开处理的。PET-MR 研究和开发社区正在积极研究使用两种成像技术的协同作用来提高断层扫描重建精度的方法，但是，实际应用在很大程度上依赖于软件。PET-MR 社区可用的开源软件——例如 PET 包 (STIR)（Thielemans 等人，2012 年）和 MR 包 Gadgetron（Hansen 和 Sorensen，2013 年）——为新的协同 PET-MR 提供了基础软件。但是，这两个软件包是独立的，并且具有非常不同的软件架构。它们大多是用 C++ 编写的，但 PET-MR 社区的许多研究人员更熟悉脚本风格的语言，例如 Python 和 MATLAB，它们能够快速构建新型重建算法的原型。在当前情况下，研究人员很难利用 PET 和 MR 数据之间的任何协同作用。此外，来自一个领域的技术不容易应用于另一领域。解决方法：在SIRF中，大部分计算由可用的可以使用多线程和GPU的高级开源重构和注册软件（目前为STIR、Gadgetron和NiftyReg）执行。SIRF C++ 代码在这些现有库之上提供了一个薄层。SIRF 层具有统一的数据容器和访问机制。这个 C++ 层为简单直观的 Python 和 MATLAB 界面提供了基础，使用户能够仅使用这些脚本语言快速开发和测试他们的重建算法。同时，