TR&D Project 2: Virtual Scanners

摘要-TRD 2：虚拟扫描仪 虚拟成像试验（VITs）为计算机断层扫描（CT）研究提供了一种强有力的替代方案 技术与人类的主题。由于试验是在计算机上进行的，虚拟试验需要快速和逼真的 CT模拟器。然而，目前的CT模拟器是不足以满足这一需要，由于有限的代表性 实际CT采集过程的复杂性和速度慢。使用蒙特卡罗方法的模拟器是最佳的， 精确地对图像获取过程建模，但是对于模拟高分辨率图像来说太慢。 其他射线追踪方法更快，但无法提供吸收辐射剂量的实际估计， 这是CT成像中非常重要的因素。大多数模拟器在建模特定的能力方面受到进一步的限制 CT品牌和型号，这将是必不可少的，以代表一个实际的临床CT成像方案。 本项目开发并提供了一个新的CT仿真平台，以满足所需的吞吐量和真实性 虚拟成像试验。该平台结合了高空间/时间细节（由ray提供）的优点， 跟踪）、精确的辐射剂量和散射估计（由Monte Carlo提供）、速度（由GPU提供 计算和熟练的编程）和特异性（基于精确系统的CT子组件建模 CT制造商的规格）。该项目已经为一台CT扫描仪制作了原型， 将原型转换为适用于多个CT系统的全面CT模拟器平台。 该项目的具体目标是（1）详细建模CT采集子组件;（2）建模CT 用于估计初级信号、散射和辐射剂量的采集方案;（3）实现用于 集成、图像形成和验证;以及（4）构建模块化接口，以有效使用 模拟器模拟将包括特定于制造商的、用户定义的和通用的（即，制造商- 中性）CT系统和重建算法、探测器几何结构和模型（包括光子计数 检测器），对采集规范的完全用户控制（即，来自TRD 1的虚拟患者输入，CT扫描仪， 协议、kV、mA、重建等），和一个用户友好的模块化界面，具有GUI和基于脚本的实用程序。 这项工作将提供一个第一的快速和准确的CT模拟器与扫描仪特定的，用户- 可定制的通用3D和4D建模功能，可模拟重建图像 和吸收的辐射剂量。用户将能够利用模拟器来研究各种CT技术 和应用，诸如与辐射剂量优化、图像质量评估以及 心脏和呼吸运动导致图像变形。该模拟器将实现基于任务的设计， 评估新的CT系统和基于人工智能（AI）的培训， 逼真的图像数据集，其复制了临床图像的真实性，并具有已知背景的附加优势 真相CT模拟平台，结合虚拟患者套件（TRD 1）和虚拟阅片器（TRD 3） 由中心提供的，形成必要的工具集，使虚拟成像试验在CT。

ABSTRACT – TRD2: Virtual Scanners Virtual Imaging Trials (VITs) offer a powerful alternative to conducting studies of computed tomography (CT) technologies with human subjects. With the trial taking place in silico, virtual trials require a fast and realistic CT simulator. However, current CT simulators are inadequate to meet this need due to limited representation of the actual CT acquisition processes and slow speed. Simulators using Monte Carlo methods are optimal in accurately modeling the image acquisition process but too slow for simulating high resolution images. Alternative ray-tracing methods are faster but unable to provide realistic estimates of absorbed radiation dose, a factor of high importance in CT imaging. Most simulators are further limited in their ability to model specific CT makes and models, which would be essential to represent an actual clinical CT imaging scenario. This project develops and provides a new CT simulation platform to meet the desired throughput and realism of virtual imaging trials. The platform combines the benefits of high spatio/temporal details (provided by ray- tracing), precise radiation dose and scatter estimates (provided by Monte Carlo), speed (provided by GPU computing and proficient programing), and specificity (modeling CT subcomponents based on precise system specifications from CT manufacturers). Already prototyped for one CT scanner, this project will expand the prototype into a comprehensive CT simulator platform for multiple CT systems. The Specific Aims of the project are (1) to model CT acquisition subcomponents in detail; (2) to model CT acquisition schemes for estimating primary signal, scatter, and radiation dose; (3) to implement processes for integration, image formation, and validation; and (4) to build a modular interface to enable effective use of the simulator. The simulation will include manufacturer-specific, user-defined, and generic (i.e., manufacturer- neutral) CT systems and reconstruction algorithms, detector geometry and models (including photon-counting detectors), full user-control over acquisition specifications (i.e., virtual patient input from TRD1, CT scanner, protocol, kV, mA, recon, etc.), and a user-friendly modular interface with both GUI and script-based utility. This work will provide a first-of-its-kind rapid and accurate CT simulator with scanner-specific, user- customizable, and generic 3D and 4D modeling capabilities, which can simulate both reconstructed images and absorbed radiation dose. Users will be able to utilize the simulator to study a variety of CT technologies and applications, such as those pertaining to radiation dose optimization, image quality assessment, and image deformation from cardiac and respiratory motion. The simulator would enable task-based design and evaluation of new CT systems and artificial intelligence (AI)-based training through generating large-scale realistic image datasets that replicate the realism of clinical images with the added advantage of known ground truth. The CT simulation platform, combined with the suite of virtual patients (TRD1) and virtual readers (TRD3) offered by the Center, form the essential toolset to enable virtual imaging trials in CT.