A Multi-Disciplinary Approach to Solve the Inverse Problem of Electro- and Magnetocardiography

解决心电图和心磁图反问题的多学科方法

• 批准号: 191020717
• 负责人: Professor Dr. Olaf Dössel, Ph.D.
• 金额: --
• 依托单位: School of Mathematics and Statistics
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2011
• 资助国家: 德国
• 起止时间: 2010-12-31 至 2014-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/191020717?language=en
• 关键词: Multi; Disciplinary; Approach; Solve; Inverse

In electrocardiography (ECG), the heart is studied by interpreting voltages measured on the body surface. The spatial accuracy of the ECG can be improved by adding more sensors and by modeling the signals with the help of physics and mathematics. In the inverse problem of ECG, the aim is to estimate the sources of the cardiac electric sources or the electric potential on the surface of the heart from the measured signal at the body surface. This problem is illposed: simplifying assumptions, a-priori information, and regularization are needed.The aim of this project is to increase the value of ECG as a tool for cardiac diagnosis by developing methods for solving the inverse problem of electrocardiography.The first research lead will concentrate on an increase in the reconstruction quality using model-based spatio-temporal regularization techniques. The second approach aims to assess the capability of electro- and magnetocardiographic imaging of reconstructing clinically relevant information in the presence of incomplete models and data. In a third lead, the focus will be on new mathematical approaches like making the solver faster and more effective, which can be achieved by a decomposition of the large-scale ill-conditioned problem. Another aspect is the use of different error norms and regularization schemes.

在心电图（ECG）中，通过解释在身体表面上测量的电压来研究心脏。通过添加更多的传感器并借助物理和数学对信号进行建模，可以提高心电图的空间精度。在ECG的反问题中，目的是估算心脏电源的来源或从人体表面的测量信号中估算心脏表面上的电位。这个问题的问题不足：需要简化的假设，A-PRIORI信息和正则化。该项目的目的是通过开发用于解决电心心电图反向问题的方法来提高ECG作为心脏诊断的工具的价值。首次研究铅将使用基于模型的Spatio-spatio-tempor-tempor正常化技术来解决重建质量的提高。第二种方法旨在评估在不完整模型和数据存在下重建临床相关信息的电心和磁性成像的能力。在第三个领导者中，重点将放在新的数学方法上，例如使求解器更快，更有效，这可以通过分解大规模条件不良问题来实现。另一个方面是使用不同的误差规范和正则化方案。