Radiation-induced Impacts on Cell Adhesion and Its Cell Cycle Dependence

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  • Seino Ryosuke
    Graduate School of Health Sciences, Hokkaido University
  • Fukunaga Hisanori
    Department of Biomedical Science and Engineering, Faculty of Health Sciences, Hokkaido University

Bibliographic Information

Other Title
  • X線被ばく後の細胞接着面積の変化と細胞周期依存性—深層学習に基づく画像解析の放射線生物学への応用—

Abstract

<p>In recent years, the use of artificial intelligence in imaging analysis has become increasingly popular. In particular, algorithms based on deep learning, a type of machine learning, are considered promising tools. In this study, we used Cellpose 2.0, a cell segmentation algorithm based on deep learning, to analyze changes in cell adhesion following exposure to X-rays in synchronous HeLa cells. We found that the cell adhesion area of G1-phase cells increased after irradiation, while that of G2-phase cells decreased.</p>

Journal

  • RADIOISOTOPES

    RADIOISOTOPES 73 (1), 61-67, 2024-03-15

    Japan Radioisotope Association

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