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Electrical Impedance Tomography for Industrial Detection and Medical Diagnosis

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 1072

Special Issue Editor


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Guest Editor
School of Electrical Automation and Information Engineering, Tianjin University, Tianjin, China
Interests: medical diagnosis based on tomography; computer vision technique; pattern recognition and information system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Owing to its advantages of real time, noninvasiveness, and low cost, electrical impedance tomography (EIT) has been applied in many fields, such as bedside monitoring in medical treatment and online detecting in industrial applications. But the low imaging quality and unstable parameters greatly affect the EIT level. Any progresses among the EIT algorithms, practical applications, and so on, will be helpful for Industrial Detection and Medical Diagnosis. This Special Issue welcomes the submission of research covering the following topics: EIT imaging, advanced EIT algorithm, EIT data processing, sensor modeling, and so on.

Dr. Shihong Yue
Guest Editor

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Keywords

  • EIT
  • industrial detection
  • medical diagnosis

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Published Papers (1 paper)

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Research

22 pages, 132889 KiB  
Article
Application of Bivariate Reproducing Kernel-Based Best Interpolation Method in Electrical Tomography
by Yongguang Tan, Jingqi Wang, Junqi Yu, Boqi Wu, Jinchao Shen and Xiangchen Guo
Sensors 2024, 24(22), 7165; https://doi.org/10.3390/s24227165 - 7 Nov 2024
Viewed by 795
Abstract
Electrical Tomography (ET) technology is widely used in multiphase flow detection due to its advantages of low cost, visualization, fast response, non-radiation, and non-invasiveness. However, ill-posed solutions lead to low image reconstruction resolution, which limits its practical engineering applications. Although existing interpolation approximation [...] Read more.
Electrical Tomography (ET) technology is widely used in multiphase flow detection due to its advantages of low cost, visualization, fast response, non-radiation, and non-invasiveness. However, ill-posed solutions lead to low image reconstruction resolution, which limits its practical engineering applications. Although existing interpolation approximation algorithms can alleviate the effects of the ill-posed solutions to some extent, the imaging results remain suboptimal due to the limited approximation capability of these methods. This paper proposes a Bivariate Reproducing Kernel-Based Best Interpolation (BRKBI) method, which offers smaller approximation errors and clearer image reconstruction quality compared to existing methods. The effectiveness of the BRKBI method is validated through theoretical analysis and experimental comparisons. Full article
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