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Vol. 34, No. 8(3), S&M3042

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Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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Sensors and Materials, Volume 36, Number 6(4) (2024)
Copyright(C) MYU K.K.
pp. 2557-2568
S&M3686 Research Paper of Special Issue
https://doi.org/10.18494/SAM5013
Published: June 27, 2024

Analysis of Correlation between Electron Diffraction Images of Corneocytes and Skin Barrier Properties by Multilayer Perceptron and Convolutional Neural Network [PDF]

Yoshifumi Takahashi, Yusuke Iida, and Hiromitsu Nakazawa

(Received January 31, 2024; Accepted June 21, 2024)

Keywords: electron diffraction image, transepidermal water loss, skin barrier, multilayer perceptron, convolutional neural network

Skin parameters such as transepidermal water loss (TEWL) and water content are important information in relation to the skin barrier function of the human body. It was reported that the structures of corneocytes and intercellular lipids are important for the skin barrier. In a recent study, it has been found that there is a correlation between the packing structure of intercellular lipids and TEWL. However, there have been no studies that focused on the correlation between the structures of individual cells and skin parameters. On the other hand, the advances in sensor technology have made it possible to acquire high-resolution 2D electron diffraction (ED) images. Thus, we attempted to examine the relationship between the 2D ED images of corneocytes and the TEWL or water content values, which is difficult with the rule-based analysis, by introducing a deep learning model. Our results showed that the highest prediction accuracy of 13.92 ± 0.57% as the error rate is achieved for water content with a diffraction image rather than with 1D ED profiles, which suggests that spatial anisotropy in a 2D image may contribute to the skin barrier function.

Corresponding author: Yoshifumi Takahashi


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Cite this article
Yoshifumi Takahashi, Yusuke Iida, and Hiromitsu Nakazawa, Analysis of Correlation between Electron Diffraction Images of Corneocytes and Skin Barrier Properties by Multilayer Perceptron and Convolutional Neural Network, Sens. Mater., Vol. 36, No. 6, 2024, p. 2557-2568.



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