Revolutionizing Medical Imaging (ReImagine) through Ubiquitous, Low-Dose, Automated Computed Tomography Diagnostic Systems

通过无处不在的低剂量自动计算机断层扫描诊断系统彻底改变医学成像 (ReImagine)

• 批准号: EP/W004445/1
• 负责人: Samuel Stranks
• 金额: $ 38.53万
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FW004445%2F1
• 关键词: Revolutionizing; Medical; Imaging; ReImagine; through

Imagine a world in which every individual can be routinely and extensively health monitored, in a time-efficient and safe manner, without having to visit an oversubscribed, centralised medical centre with limited access and appointment flexibility. Imagine a new clinical paradigm where early diagnosis becomes the standard, even in remote areas, within low-income demographics and for international travel, due to ubiquitous, modular, high-resolution X-ray imaging systems with automated diagnosis and live reporting; where frequent imaging contributes to a large diagnostic portfolio of individuals over time (whilst maintaining privacy) and advanced artificial-intelligence (AI)-based algorithms use these anonymous data sets acquired across the population to identify extremely early stages of disease - transforming preventative medicine as we know it. This is the 2050 that ReImagine will enable. We will revolutionise the use of X-rays for medical imaging through low-dose, high-resolution and inexpensive computed tomography (CT) scanners, where highly innovative hardware and software components will be developed side-by-side to enable automated all-in-one pre-symptomatic diagnosis. Our vision will be enabled by developing highly sensitive X-ray detectors using scalable halide perovskite (PVK) semiconductors - materials currently making impact as disruptive photovoltaic (PV) technologies - for phase contrast X-ray imaging, in conjunction with AI-driven algorithms for image reconstruction, lesion detection and segmentation. This will realise quicker and more efficient healthcare delivery and prevent disease spread through extremely early detection of disease (e.g., those otherwise responsible for future pandemics) and for routine follow-up of oncology patients (e.g. early detection of cancer recurrence). To realise this extremely challenging vision - combining breakthroughs in hardware, software and end-user application - we have uniquely assembled a world-leading, cross-cutting team from the Universities of Cambridge, Loughborough and Leicester, together with academic partners at the University of Leiden and industry partners in GE Healthcare, Scintacor, Cheyney and Immaterials Labs, bringing combined expertise spanning materials synthesis and scaling, characterisation and modelling, device assembly, detector physics, mathematics, CT systems development, and clinical radiology. The hardware will be interweaved with the software and algorithm development, with both guided by clinical insight, industry and case studies to ensure fit for end users.

想象一下，在这样一个世界里，每个人都可以以一种高效、安全的方式进行常规和广泛的健康监测，而不必去一个超额预订的、集中的医疗中心，那里的访问和预约灵活性有限。想象一个新的临床模式，早期诊断成为标准，即使在偏远地区，低收入人口和国际旅行中，由于无处不在，模块化，高分辨率X射线成像系统，自动诊断和实时报告;随着时间的推移，频繁的成像有助于大量的个人诊断组合（同时保持隐私）和先进的基于人工智能（AI）的算法使用这些在人群中获得的匿名数据集来识别疾病的极早期阶段-这是ReImagine将实现的2050年。我们将通过低剂量，高分辨率和廉价的计算机断层扫描（CT）扫描仪彻底改变X射线在医学成像中的使用，其中高度创新的硬件和软件组件将同时开发，以实现自动化的一体化症状前诊断。我们的愿景将通过开发高灵敏度的X射线探测器来实现，该探测器使用可扩展的卤化物钙钛矿（PVK）半导体-目前作为破坏性光伏（PV）技术产生影响的材料-用于相位对比X射线成像，结合用于图像重建，病变检测和分割的AI驱动算法。这将实现更快和更有效的医疗保健服务，并通过极早期的疾病检测（例如，那些对未来的流行病负有责任的人）和肿瘤患者的常规随访（例如癌症复发的早期检测）。为了实现这一极具挑战性的愿景--结合硬件、软件和最终用户应用的突破--我们独一无二地组建了一支世界领先的跨领域团队，来自剑桥大学、拉夫堡大学和莱斯特大学，以及莱顿大学的学术合作伙伴和GE Healthcare、Scintacor、Cheyney和Imaterials Labs的行业合作伙伴，带来了涵盖材料合成和缩放的综合专业知识，表征和建模、器械组装、探测器物理学、数学、CT系统开发和临床放射学。硬件将与软件和算法开发交织在一起，两者都以临床见解、行业和案例研究为指导，以确保适合最终用户。

项目成果

Navigating the challenges in creating complex data systems: a development philosophy

应对创建复杂数据系统的挑战：开发理念

• 发表时间: 2023
• 期刊: Nature Machine Intelligence
• 影响因子: 23.8
• 作者: Dittmer S

Halide perovskites scintillators: unique promise and current limitations.

卤化物钙钛矿闪烁体：独特的前景和当前的局限性。

• DOI: 10.17863/cam.70692
• 发表时间: 2021
• 作者: Moseley O

On Krylov methods for large-scale CBCT reconstruction

• DOI: 10.1088/1361-6560/acd616
• 发表时间: 2023-08-07
• 期刊: PHYSICS IN MEDICINE AND BIOLOGY
• 影响因子: 3.5
• 作者: Landman，Malena Sabate;Biguri，Ander;Schonlieb，Carola-Bibiane
• 通讯作者: Schonlieb，Carola-Bibiane

Development and Characterisation of Halide Perovskite Visible Light and X-Ray Detection Devices

卤化物钙钛矿可见光和 X 射线检测装置的开发和表征

• 发表时间: 2023
• 作者: Moseley O D

The Electronic Disorder Landscape of Mixed Halide Perovskites.

• DOI: 10.1021/acsenergylett.2c02352
• 发表时间: 2023-01-13
• 期刊: ACS ENERGY LETTERS
• 影响因子: 22
• 作者: Liu, Yun;Banon, Jean-Philippe;Frohna, Kyle;Chiang, Yu-Hsien;Tumen-Ulzii, Ganbaatar;Stranks, Samuel D.;Filoche, Marcel;Friend, Richard H.
• 通讯作者: Friend, Richard H.