Optimal Design for Inverse Problems in Biomedical Engineering

生物医学工程反问题的优化设计

• 批准号: 2226719
• 金额: --
• 依托单位: Swansea University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2226719
• 关键词: Optimal; Design; Inverse; Problems; Biomedical

Mathematical models in biomedical engineering, for e.g. computational models of haemodynamics (blood flow), often have a large number of unknown parameters. These parameters must be estimated through clinical measurements acquired individually in each patient. However, it is not clear which measurements are most informative about the parameters and which parameters are most relevant to answer a given clinical question. This project will develop a framework for this problem of 'optimal design' through recent developments in probabilistic analysis and information theory with a particular focus on problems encountered in biomedical engineering. Key aims of the project are:1. To develop a framework for 'optimal design' using information theoretic measures.2. To apply the framework on biomedical engineering models: ionic models for cardiac cells and haemodynamics models for blood flow.The developed framework and its applications will help in determining which quantities, for example a combination of clinical measurements, are most informative about a particular clinical question, for example the diagnosis of a particular disease.

生物医学工程中的数学模型，例如血液动力学（血流）的计算模型，通常具有大量的未知参数。这些参数必须通过在每个患者中单独获得的临床测量来估计。然而，尚不清楚哪些测量值最能提供有关参数的信息，以及哪些参数与回答给定的临床问题最相关。本项目将通过概率分析和信息理论的最新发展，特别关注生物医学工程中遇到的问题，为“优化设计”问题制定一个框架。该项目的主要目标是：1。发展一个使用资讯论测量的最佳设计架构.将该框架应用于生物医学工程模型：心脏细胞的离子模型和血流的血液动力学模型。开发的框架及其应用将有助于确定哪些量，例如临床测量的组合，对于特定临床问题（例如特定疾病的诊断）提供最多信息。