在电阻抗断层扫描中使用神经网络和深度学习算法

G. Kłosowski, T. Rymarczyk
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引用次数: 32

摘要

本文介绍了人工神经网络和卷积神经网络在阻抗层析成像中的应用。机器学习方法可以用来教计算机不同的技术问题。传统的人工神经网络在断层扫描中的有效使用是可能的,能够有效地可视化物体。本文完成了在电阻抗断层成像中实现深度学习方法的第一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using neural networks and deep learning algorithms in electrical impedance tomography
This paper refers to the cases of the use of Artificial Neural Networks and Convolutional Neural Networks in impedance tomography. Machine Learning methods can be used to teach computers different technical problems. The efficient use of conventional artificial neural networks in tomography is possible able to effectively visualize objects. The first step of implementation Deep Learning methods in Electrical Impedance Tomography was performed in this work.
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