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International Symposium on Security and Privacy in Social Networks and Big Data

SocialSec 2020: Security and Privacy in Social Networks and Big Data pp 420–432Cite as

Forward Calculation for Improving the Sensitivity of Multiple Perturbations in Magnetic Induction Tomography Based on Brain Tissue Structure

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1298))

Abstract

Magnetic Induction Tomography (MIT) is a non-invasive and contactless electromagnetic imaging method, which is especially suitable for medical monitoring. The low sensitivity of the central region of the measured target has always restricted the application of MIT in practice. In this paper, based on the analysis of the biological structure of human brain, the sensitivity of the brain structure to the forward problem is studied. The experimental parameters are certain, the measurement model is established, and the perturbation conductivity value is calculated and compared in the case of multiple perturbations to the target object under different conditions. The result shows that, under the ideal condition of parameter setting, adding perturbations to the target region can improve the sensitivity within the region can provide a new way of thinking for the research of improving the sensitivity in MIT.

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Authors and Affiliations

  1. Shenyang Aerospace University, Shenyang, 110136, Liaoning, China

    Yi Lv

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  1. Yi Lv
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Correspondence to Yi Lv .

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Editors and Affiliations

  1. Swinburne University of Technology, Melbourne, VIC, Australia

    Yang Xiang

  2. Nankai University, Tianjin, China

    Zheli Liu

  3. Guangzhou University, Guangzhou, China

    Jin Li

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Lv, Y. (2020). Forward Calculation for Improving the Sensitivity of Multiple Perturbations in Magnetic Induction Tomography Based on Brain Tissue Structure. In: Xiang, Y., Liu, Z., Li, J. (eds) Security and Privacy in Social Networks and Big Data. SocialSec 2020. Communications in Computer and Information Science, vol 1298. Springer, Singapore. https://doi.org/10.1007/978-981-15-9031-3_37

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  • DOI: https://doi.org/10.1007/978-981-15-9031-3_37

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-9030-6

  • Online ISBN: 978-981-15-9031-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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