IF 3.2
Medical physics Pub Date : 2025-10-01 DOI:10.1002/mp.70066
Amar Kavuri, Milo Fryling, Nicholas Felice, Lior Malvin, Darin P Clark, Ehsan Samei, Ehsan Abadi
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摘要

背景:虚拟成像试验(VIT)通过患者和扫描设备的计算模型促进医学成像实验。为了在整个医学成像社区广泛采用,VIT工具不仅应该准确,而且应该健壮且用户友好。目的:开发一个经过验证的端到端CT模拟框架,该框架具有基于脚本和图形用户界面(gui),可在不同的计算环境中进行简单的安装和强大的性能打包。方法:将先前验证的CT模拟器(DukeSim)打包成端到端框架,其中包含四个主要组件:(1)基于临床扫描仪控制台的基于web的GUI, (2) Python包装脚本作为灵活的入口点,(3)利用光线追踪和蒙特卡罗方法的基于物理的CT投影仪,以及(4)支持过滤反投影和迭代技术的供应商中立重建模块(MCR Toolkit)。基于NodeJS和Express服务器配置开发了基于web的GUI,用于选择协议和扫描仪配置并启动CT模拟。集成的DukeSim软件构建在三种类型的软件包中,具有严格的版本控制、测试、错误跟踪和发布过程。此外,通过开发模拟传统CT扫描仪属性的样本扫描仪模型,验证了该软件的功能和潜在效用。结果:成功开发了集成的CT模拟框架,实现了虚拟成像试验的无缝采用和广泛适用性。此外,遗留扫描仪的建模和验证证明了该框架能够准确地表示各种临床相关的扫描仪。结论:这项工作代表了CT模拟工具的重大进步,为虚拟成像试验提供了端到端的、经过验证的、强大的解决方案。该软件可以灵活地模拟各种CT技术,结合其用户友好的界面和经过验证的准确性,使其成为推进CT技术开发、评估和优化研究的宝贵工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An end-to-end CT simulation framework with graphical user interface and sample scanner models.

Background: Virtual imaging trials (VIT) facilitate medical imaging experimentation through computational models of patients and scanning equipment. For broad adoption across the medical imaging community, VIT tools should not only be accurate but also robust and user-friendly.

Purpose: To develop a validated, end-to-end CT simulation framework with script-based and graphical user interfaces (GUIs), packaged for simple installation and robust performance across diverse computing environments.

Methods: A previously-validated CT simulator (DukeSim) was packaged into an end-to-end framework with four major components: (1) a web-based GUI inspired by clinical scanner consoles, (2) a Python wrapper script serving as a flexible entry point, (3) a physics-based CT projector utilizing ray-tracing and Monte Carlo methods, and (4) a vendor-neutral reconstruction module (MCR Toolkit) supporting both filtered back-projection and iterative techniques. The web-based GUI was developed based on NodeJS and Express server configuration to select the protocol and scanner configurations and to initiate the CT simulations. The integrated DukeSim software was built in three types of packages, with rigorous version control, testing, bug tracking, and release processes. Further, the software's capabilities and potential utilities were demonstrated by developing sample scanner models mimicking the attributes of legacy CT scanners.

Results: The integrated CT simulation framework was successfully developed, enabling seamless adoption and broad applicability in virtual imaging trials. Additionally, the modeling and validation of legacy scanners demonstrated the framework's capability to accurately represent a variety of clinically relevant scanners.

Conclusions: This work represents a major advancement in CT simulation tools, providing an end-to-end, validated, and robust solution for virtual imaging trials. The software's flexibility to model various CT technologies, combined with its user-friendly interface and validated accuracy, positions it as a valuable tool for advancing research in CT technology development, assessment, and optimization.

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