Abstract Optimal design of electronic devices such as sensors is essential since it results in more accurate output at the shortest possible time. In this work, we develop optimal Bayesian inversion for electrical impedance tomography (EIT) technology in order to improve the quality of medical images generated by EIT and to put this promising imaging technology into practice. We optimize Bayesian experimental design by maximizing the expected information gain in the Bayesian inversion process in order to design optimal experiments and obtain the most informative data about the unknown parameters. We present optimal experimental designs including optimal frequency and optimal electrode configuration, all of which result in the most accurate estimation of the unknown quantities to date and high-resolution EIT medical images, which are crucial for diagnostic purposes. Numerical results show the efficiency of the proposed optimal Bayesian inversion method for the EIT inverse problem.

中文翻译：

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医学成像中电阻抗断层扫描的最佳贝叶斯实验设计

摘要 传感器等电子设备的优化设计至关重要，因为它可以在尽可能短的时间内产生更准确的输出。在这项工作中，我们开发了电阻抗断层扫描 (EIT) 技术的最佳贝叶斯反演，以提高 EIT 生成的医学图像的质量，并将这种有前途的成像技术付诸实践。我们通过最大化贝叶斯反演过程中的预期信息增益来优化贝叶斯实验设计，以设计最佳实验并​​获得有关未知参数的信息最多的数据。我们提出了最佳实验设计，包括最佳频率和最佳电极配置，所有这些都可以最准确地估计迄今为止的未知量和高分辨率 EIT 医学图像，这对于诊断目的至关重要。数值结果表明了所提出的最优贝叶斯反演方法对于 EIT 逆问题的效率。