Ultra-sensitive 3D molecular assays using total body PET and deep learning

使用全身 PET 和深度学习进行超灵敏 3D 分子检测

• 批准号: DP230102070
• 负责人: Prof Steven Meikle
• 金额: $ 39.84万
• 依托单位: The University of Sydney
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2023
• 资助国家: 澳大利亚
• 起止时间: 2023-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP230102070
• 关键词: Ultra; sensitive; 3D; molecular; assays

Recent advances in biomedical engineering have led to the development of Total Body Positron Emission Tomography (TB-PET), the most sensitive imaging device to date. Despite these impressive engineering advances, computational methods lag far behind and model-based approaches cannot deal with the complexity or volume of data these systems produce. We will develop new computational methods based on deep learning and statistical methods that fully exploit the richness and complexity of the data generated by TB-PET, enabling 3D quantitative assays of molecular processes throughout the entire human body with unparalleled sensitivity. The technology we create will open up new capability for the study of complex physiological systems.

生物医学工程的最新进展导致了全身正电子发射断层扫描（TB-PET）的发展，这是迄今为止最灵敏的成像设备。尽管有这些令人印象深刻的工程进步，但计算方法远远落后，基于模型的方法无法处理这些系统产生的复杂性或数据量。我们将开发基于深度学习和统计方法的新计算方法，充分利用TB-PET生成的数据的丰富性和复杂性，以无与伦比的灵敏度对整个人体的分子过程进行3D定量分析。我们创造的技术将为复杂生理系统的研究开辟新的能力。