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ID 65253
フルテキストURL
著者
Takao, Daisuke Department of Cell Biology and Anatomy and International Research Center for Neurointelligence (WPI-IRCN), Graduate School of Medicine, The University of Tokyo
Kyunai, Yuki M. Faculty of Engineering, Department of Applied Chemistry and Biotechnology, Okayama University
Okada, Yasushi Department of Cell Biology and Anatomy and International Research Center for Neurointelligence (WPI-IRCN), Graduate School of Medicine, The University of Tokyo
Satoh, Ayano Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University
抄録
The visual classification of cell images according to differences in the spatial patterns of subcellular structure is an important methodology in cell and developmental biology. Experimental perturbation of cell function can induce changes in the spatial distribution of organelles and their associated markers or labels. Here, we demonstrate how to achieve accurate, unbiased, high-throughput image classification using an artificial intelligence (AI) algorithm. We show that a convolutional neural network (CNN) algorithm can classify distinct patterns of Golgi images after drug or siRNA treatments, and we review our methods from cell preparation to image acquisition and CNN analysis.
キーワード
Convolutional neural network
Image classification
Golgins
Golgi
Microtubule
備考
This is an Accepted Manuscript of a protocol published by Humana New York.
Molecular Biology, vol 2557.
This fulltext file will be available in Dec. 2024.
発行日
2022-12-14
出版物タイトル
Golgi
出版者
Humana New York
開始ページ
275
終了ページ
285
資料タイプ
図書
言語
英語
OAI-PMH Set
岡山大学
著作権者
© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature
論文のバージョン
author
PubMed ID
DOI
関連URL
isVersionOf https://doi.org/10.1007/978-1-0716-2639-9_18
Citation
Takao, D., Kyunai, Y.M., Okada, Y., Satoh, A. (2023). A Primer on Deep Learning-Based Cellular Image Classification of Changes in the Spatial Distribution of the Golgi Apparatus After Experimental Manipulation. In: Wang, Y., Lupashin, V.V., Graham, T.R. (eds) Golgi. Methods in Molecular Biology, vol 2557. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2639-9_18
助成機関名
Japan Society for the Promotion of Science
助成番号
18K06233
18K06133
19H05974
19H05975
21K06163
21H04708
21H05028