ULTRA-HIGH RESOLUTION MODELLING OF THE HUMAN BRAIN USING MULTISCALE, MULTIMODAL IMAGING AND AI

使用多尺度、多模态成像和人工智能对人脑进行超高分辨率建模

• 批准号: 2722584
• 金额: --
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2722584
• 关键词: ULTRA; RESOLUTION; MODELLING; HUMAN; BRAIN

1. Context of the research including potential impactResearchers at UCL have developed a new X-ray imaging method called Hierarchical Phase-Contrast Tomography (HiP-CT), which allows imaging whole human organs in detail up to the cellular level. HiP-CT is an X-ray phase propagation technique that uses the European Synchrotron Radiation Facility (ESRF) Extremely Brilliant Source to perform non-destructive, three-dimensional (3D) scans with hierarchically increasing resolution at any location in whole human organs, down to 1 um/voxel in Volumes of Interest. As such, these imaging data not only provide a novel view of the complex hierarchical structure of the human brain but could also provide a detailed understanding of the biological processes at work during neurodegenerative diseases which are difficult to diagnose.This PhD will develop advanced AI tools for data processing, meaningful interpretation and analysis, and translation of these high-resolution images to clinical use.2. Aims and objectivesThe goal of this project is to enhance our understanding of the structure of white matter tracts and blood vessels in the brain, both in healthy individuals and in those with neurodegenerative conditions. This will be done by developing advanced computational techniques, such as large-scale AI, to analyze multi-resolution images obtained from a synchrotron and then correlating these images with MRI images to realise clinical use in the assessment of a neurodegenerative disease such as Alzheimer's.3. Novelty of the research methodologyThe HiP-CT imaging method enables imaging of the human brain with a resolution of up to 300 times greater than the current highest resolution MRI scans and so requires bespoke computational methods to be developed for modelling brain structure. These imaging data are unique worldwide and will be correlated to clinical MRI images to improve the current models of white matter tract orientation and vascular architecture, in healthy and neurodegenerative cases.4. Alignment to EPSRC's strategies and research areasThe project aligns with the priorities of the EPSRC Healthcare Technologies Theme, specifically around Novel imaging technologies. This research will support the development of advanced AI tools for data processing, making sense of complex imaging data, understanding underlying pathology and monitoring progression of neurodegenerative diseases.5.Any companies or collaborators involvedChan Zuckerberg Initiative

1。研究的上下文包括UCL的潜在不良研究人员，开发了一种新的X射线成像方法，称为层次相对比层析成像（HIP-CT），该方法允许将整个人体器官详细成像至细胞水平。 HIP-CT是一种X射线相位传播技术，它使用欧洲同步加速器辐射设施（ESRF）极出色的来源来执行非破坏性的三维（3D）扫描，在整个人类器官中的任何位置的分辨率下降，低于1 UM/VOXEL的任何位置。因此，这些成像数据不仅提供了人类大脑复杂的分层结构的新颖观点，而且还可以详细了解很难诊断的神经退行性疾病期间工作中工作中的生物学过程。该博士将开发出高级的AI处理工具，用于数据处理，有意义的解释，分析和分析，并将这些高分辨率分析到这些临床图像进行临床图像。2。该项目的目的和客观性目标是增强我们对健康个体和神经退行性疾病的人的大脑中白质和血管结构的理解。这将通过开发高级计算技术（例如大规模AI）来分析从同步加速器获得的多分辨率图像，然后将这些图像与MRI图像相关联，以实现在评估神经退行性疾病（例如阿尔茨海默氏症）中的临床使用。研究方法的新颖性HIP-CT成像方法可以使人脑的成像比当前最高分辨率的MRI扫描高300倍，因此需要开发定制的计算方法来建模大脑结构。这些成像数据在全球范围内是独特的，并且将与临床MRI图像相关，以改善健康和神经退行性病例中的白质区域方向和血管结构的当前模型。4。与EPSRC的策略和研究领域保持一致，该项目与EPSRC Healthcare Technologies主题的优先级相吻合，特别是围绕新型成像技术。这项研究将支持开发用于数据处理的高级AI工具，使复杂的成像数据有意义，理解潜在的病理学并监测神经退行性疾病的进展。5.HoneCompanies或Complocanters涉及Chan Zuckerberg Initiative Initiative