Application of a regressive neural network with autoencoder for monochromatic images in ultrasound tomography

被引：0
|
作者：
Rymarczyk, Tomasz [1 ,2 ]
Klosowski, Grzegorz [3 ]
Cieplak, Tomasz [3 ]
Kozlowski, Edward [3 ]
Kania, Konrad [1 ]
机构：
[1] Netrix SA, Ctr Res & Dev, Lublin, Poland
[2] Univ Econ & Innovat Lublin, Lublin, Poland
[3] Lublin Univ Technol, Fac Management, Lublin, Poland
来源：
2019 APPLICATIONS OF ELECTROMAGNETICS IN MODERN ENGINEERING AND MEDICINE (PTZE) | 2019年
关键词：
ultrasound tomography; artificial neural networks; process tomography; autoencoders;
D O I：
10.23919/ptze.2019.8781750
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The article presents a novel approach to ultrasound tomography in industrial applications. In order to visualize the interior of a tank (reactor) filled with tap water, a single neural network enhanced with autoencoder was used. A novelty is the use of an autoencoder to improve the quality of the measurement vector. Thanks to the use of the autoencoder for denoising the input measurements in connection with the appropriately adapted neural network, the quality of the output image was improved. A robust algorithm was developed that properly reconstructs hidden objects in monochrome images with high efficiency.
引用
收藏
页码：156 / 160
页数：5
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