The article presents machine learning methods in the field of reconstruction of tomographic images. The presented research results show that electric tomography makes it possible to analyze objects without interfering with them. The work focused mainly on electrical impedance tomography and image reconstruction using deterministic methods and machine learning, reconstruction results were compared and various numerical models were used. The main advantage of the presented solution is the ability to analyze spatial data and high speed of processing. The implemented algorithm based on logistic regression is promising in image reconstruction. In addition, the elastic net method was used to solve the problem of selecting input variables in the regression model.

中文翻译：

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在电阻抗断层扫描中应用逻辑回归分析被检物体的电导率

本文介绍了层析图像重建领域的机器学习方法。提出的研究结果表明，电子断层扫描可以在不干扰物体的情况下分析物体。这项工作主要集中在电阻抗断层成像以及使用确定性方法和机器学习进行图像重建的过程中，比较了重建结果并使用了各种数值模型。所提出的解决方案的主要优点是能够分析空间数据和高速处理。基于逻辑回归的算法在图像重建中具有广阔的应用前景。另外，采用弹性网法解决了回归模型中选择输入变量的问题。