Ultraportable Stroke CT Based on Stationary Carbon Nanotube X-ray Source and Deep Learning Image Formation

项目总结 这个为期12个月的SBIR第一阶段项目的目标是开发一种成像设备，使其能够 为遭受创伤事件的患者提供高效、经济高效的中风成像。这个 预期的技术成果将是一个概念验证的头部CT成像系统，具有 秒成像速度、亚毫西弗辐射剂量和高质量图像。具有以下功能的成像系统 这种能力将解决目前在及时诊断中风患者方面的不足，以及 以更高的效率和更低的成本造福社会。这样的成像设备将使强大的 对全球头部CT成像市场的经济影响，估计约为36美元 从长远来看，这项新的成像技术可以转化为 安检、行业检查和牙科成像市场。 该项目是基于曹博士的团队在An支持下的最新研究成果 美国国家科学基金会职业奖(曹博士，2019年8月1日-31月7日，40万美元)和曹博士的 英联邦研究商业化基金(CRCF)奖(标题：《Computed 用于快速和便携式生物医学成像的无移动部件层析成像“，07/01/2017- 2019年6月30日，10万美元)。该项目在知识产权方面站稳了脚跟。技术 受到包括美国在内的弗吉尼亚理工大学的几项专利申请的保护。62/316649， 《用于自由活动动物成像的超高速显微CT》(发明人：曹国华)，以及 PCT/US2013/061049和US14/429835，“计算固定源的系统和方法 断层摄影术“(发明人：曹国华等人)Al.)。在这个项目中，团队将设计和建造一个 概念验证头部CT平台测试超便携紧凑型头部CT的可行性 基于固定式碳纳米管x射线源设计与深度学习图像 重建算法。 该项目的预期成果包括论证超快的可行性， 头模脑出血的低剂量和诊断成像能力 (ICH)，有可能通过深度学习算法自动识别ICH。一个准备好了的- 对头部CT设备样机进行优化设计，并制定相应的商业计划 将会被开发出来。

PROJECT SUMMARY The goal of this 12-month SBIR phase 1 project is developing an imaging device that will enable highly efficient and cost-effective stroke imaging for patients suffered trauma events. The expected technical outcome will be a proof-of-concept head CT imaging system with sub- second imaging speed, sub-mSv radiation dose, and high-quality images. Imaging systems with such capabilities will address the current deficiency in timely diagnosis of stroke patients, and benefit society with higher efficiency and lower cost. Such imaging device will make a strong economic impact on the global head CT imaging market, which is estimated to be about $36 billion in the U.S. In a longer term, the novel imaging technology could be translated into markets for security screening, industry inspection, and dental imaging. This project is based on the recent research results by Dr. Cao's team under the support of an NSF CAREER award (PI Dr. Cao, 08/01/2014-07/31/2019, $400,000) and a Dr. Cao's Commonwealth Research Commercialization Fund (CRCF) award (Title: “Computed Tomography Without Moving Parts for Fast and Portable Biomedical Imaging”, 07/01/2017- 06/30/2019, $100,000). The project has a strong footing in intellectual property. The technology is protected by a few patent applications at the Virginia Tech, including US. 62/316649, “Ultrafast Micro-CT for Imaging Free-Moving Animals” (Inventor: Guohua Cao), and PCT/US2013/061049 and US14/429835, “System and Method of Stationary Source Computed Tomography” (Inventor: Guohua Cao, et. al.). In this project, the team will design and build a proof-of-concept head CT platform to test the feasibility of ultraportable and compact head CT based on the stationary carbon nanotube x-ray source design and deep learning image reconstruction algorithm. The expected outcomes from this project include demonstration of the feasibility for ultrafast, low dose, and diagnostic imaging capabilities for intracerebral hemorrhage in head phantoms (ICH), with potential automatic ICH identification through deep learning algorithm. A ready-to- prototype head CT device will be optimized and designed, and a corresponding business plan will be developed.