A multi-channel reconstruction toolkit for computed tomography

用于计算机断层扫描的多通道重建工具包

• 批准号: 10605585
• 负责人: CRISTIAN T BADEA
• 金额: $ 22.63万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-02-15 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10605585
• 关键词: 3-Dimensional; Adoption; Algorithms; Alzheimer' s Disease; Anatomy; Awareness; Basic Science; Calibration; Cardiac; Clinical; Code; Collaborations; Collection; Communities; Computer software; Data; Database Management Systems; Databases; Dependence; Development; Digital Imaging and Communications in Medicine; Discrimination; Docking; Documentation; Dose; Ensure; Environment; Funding; Generations; Geometry; Grant; Heart Diseases; Image; Imaging Device; International; Knowledge; Linux; Maintenance; Malignant Neoplasms; Manuals; Medical Imaging; Metadata; Modeling; Noise; Outcome; Photons; Physiological; Programming Languages; Protocols documentation; Publications; Publishing; Pythons; Radiation Dose Unit; Reference Document; Reproducibility; Research; Research Personnel; Research Project Grants; Research Support; Resolution; Running; Site; Source; Structure; System; TensorFlow; Time; Translational Research; Translations; Universities; Work; X-Ray Computed Tomography; algorithmic methodologies; base; biological research; cone-beam computed tomography; data acquisition; deep learning; denoising; design; detector; experimental study; file format; graphical user interface; improved; innovation; open data; open source; parent grant; photon-counting detector; pre-clinical; pre-clinical research; quantitative imaging; reconstruction; research study; scripting interface; symposium; tool

Abstract According to the FDA, the recent clinical availability of photon counting detector X-ray CT (PCCT) marks the “first major imaging device advancement for computed tomography in nearly a decade” because it provides fundamental improvements in terms of image noise, spatial resolution, material discrimination, and low contrast detectability. Yet this new era of clinical PCCT follows years of preclinical research at our Quantitative Imaging and Analysis Lab at Duke University and our preliminary research projects using the NAEOTOM Alpha clinical PCCT scanner from Siemens and installed at Duke. To support these research projects and under the Aims of our funded NIA grant (1RF1AG070149; Cardiac photon counting CT and its application in studying interactions between Alzheimer's and heart disease), we are developing a GPU-based Multi-Channel Reconstruction (MCR) Toolkit for CT (channels refer to dynamic and/or multi-energy images of 3D anatomical structures). In addition to being built from the ground up to handle the unique challenges of multi-channel reconstruction, our Toolkit includes several unique features not in other open-source packages: support for translational research using the same code on both clinical and preclinical data, robust reference algorithms for performing iterative reconstruction of low-dose multi-channel CT data, and automatic data adaptation of reconstruction parameters to reduce manual parameter tuning. The objectives of this supplement are (1) to make the MCR Toolkit codebase more robust and extensible for CT experts and (2) to provide a graphical user interface and reference reconstruction protocols for those using CT to conduct other research studies. We will accomplish these objectives through three distinct aims. In Aim 1 we propose to restructure our Toolkit codebase from its current C code to object oriented code written in C++, providing native support for popular file formats, eliminating redundant code, reducing opportunities for user errors, and allowing reconstruction pipelines to be saved and shared. Aim 2 focuses on non-expert users, producing a graphical user interface for running reconstruction pipelines on acquired data and uploading image data and metadata to an XNAT database. Finally, Aim 3 focuses on community awareness, accessibility, and documentation for the MCR Toolkit, ensuring the Toolkit is available and easy to use beyond the scope of this supplement and the parent grant. Successful completion of this work will transform the MCR Toolkit from a collection of tools useful to experts in the field to a platform for open science among CT, basic science, and clinical researchers. Widespread adoption of the Toolkit is expected thanks to the unique benefits it provides for photon counting and dynamic CT which are not currently provided by open-source software alternatives.

摘要 根据FDA的说法，光子计数探测器X射线CT（PCCT）的最近临床可用性标志着 “近十年来计算机断层扫描的第一个主要成像设备进步”，因为它提供了 在图像噪声、空间分辨率、材料辨别力和低对比度方面的根本改进 可探测性然而，临床PCCT的新时代是在我们的定量成像公司进行了多年的临床前研究之后出现的。 和分析实验室在杜克大学和我们的初步研究项目使用NAEOTOM阿尔法临床 来自Siemens并安装在杜克的PCCT扫描仪。为了支持这些研究项目， 我们资助的NIA基金（1 RF 1AG 070149;心脏光子计数CT及其在研究相互作用中的应用 阿尔茨海默氏症和心脏病之间），我们正在开发一种基于GPU的多通道重建（MCR） CT工具包（通道是指3D解剖结构的动态和/或多能量图像）。此外 为了应对多渠道重建的独特挑战，我们的工具包 包含了其他开源软件包中没有的几个独特功能：支持使用 临床和临床前数据上的相同代码，用于执行迭代的稳健参考算法 低剂量多通道CT数据的重建，以及重建参数的自动数据自适应 以减少手动参数调整。本补充文件的目标是（1）使MCR工具包代码库 对于CT专家来说，更健壮和可扩展，以及（2）提供图形用户界面和参考 重建协议，为那些使用CT进行其他研究。我们将实现这些目标 通过三个不同的目标实现目标。在目标1中，我们建议从当前的Toolkit代码库中 C代码转换为用C++编写的面向对象代码，为流行的文件格式提供本机支持， 冗余代码，减少用户错误的机会，并允许保存重建管道， 共享. AIM 2主要针对非专家用户，为运行重建生成图形用户界面 在XNAT数据库中创建一个基于采集数据的管道，并将图像数据和元数据上传到XNAT数据库。第三，聚焦 关于社区意识、可访问性和MCR工具包的文档，确保工具包可用 并且易于使用，超出了本补充和父母补助金的范围。圆满完成这项工作 将MCR工具包从一个对该领域专家有用的工具集合转变为一个开放科学平台 在CT、基础科学和临床研究人员中。预计工具包将得到广泛采用， 它为光子计数和动态CT提供了独特的好处，这些好处目前还没有由开源提供 软件替代品。