GAN-Based Method for Synthesizing Multi-focus Cell Images

Ken’ich Morooka; Xueru Zhang; Shoko Miyauchi; Ryo Kurazume; Eiji Ohno

doi:10.1007/978-3-030-39770-8_8

GAN-Based Method for Synthesizing Multi-focus Cell Images

Ken’ich Morooka, Xueru Zhang, Shoko Miyauchi, Ryo Kurazume, Eiji Ohno

実世界ロボティクス

研究成果: 書籍/レポートタイプへの寄稿 › 会議への寄与

2 被引用数 (Scopus)

抄録

This paper presents a method for synthesizing multi-focus cell images by using generative adversarial networks (GANs). The proposed method, called multi-focus image GAN (MI-GAN), consists of two generators. A base image generator synthesizes a 2D base cell image from random noise. Using the generated base image, a multi-focus cell image generator produces 11 realistic multi-focus images of the cell while considering the relationships between the images acquired at successive focus points. From experimental results, MI-GAN achieves the good performance to generate realistic multi-focus cell images.

本文言語	英語
ホスト出版物のタイトル	Image and Video Technology - PSIVT 2019 International Workshops, Revised Selected Papers
編集者	Joel Janek Dabrowski, Ashfaqur Rahman, Manoranjan Paul
出版社	Springer
ページ	100-107
ページ数	8
ISBN（印刷版）	9783030397692
DOI	https://doi.org/10.1007/978-3-030-39770-8_8
出版ステータス	出版済み - 1月 1 2020
イベント	9th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2019 - Sydney, オーストラリア継続期間: 11月 18 2019 → 11月 22 2019

出版物シリーズ

名前	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
巻	11994 LNCS
ISSN（印刷版）	0302-9743
ISSN（電子版）	1611-3349

会議

会議	9th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2019
国/地域	オーストラリア
City	Sydney
Period	11/18/19 → 11/22/19

!!!All Science Journal Classification (ASJC) codes

理論的コンピュータサイエンス
コンピュータサイエンス一般

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10.1007/978-3-030-39770-8_8

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引用スタイル

Morooka, K., Zhang, X., Miyauchi, S., Kurazume, R., & Ohno, E. (2020). GAN-Based Method for Synthesizing Multi-focus Cell Images. In J. J. Dabrowski, A. Rahman, & M. Paul (Eds.), Image and Video Technology - PSIVT 2019 International Workshops, Revised Selected Papers (pp. 100-107). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11994 LNCS). Springer. https://doi.org/10.1007/978-3-030-39770-8_8

GAN-Based Method for Synthesizing Multi-focus Cell Images. / Morooka, Ken’ich; Zhang, Xueru; Miyauchi, Shoko その他.
Image and Video Technology - PSIVT 2019 International Workshops, Revised Selected Papers. ed. / Joel Janek Dabrowski; Ashfaqur Rahman; Manoranjan Paul. Springer, 2020. p. 100-107 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11994 LNCS).

研究成果: 書籍/レポートタイプへの寄稿 › 会議への寄与

Morooka, K, Zhang, X, Miyauchi, S , Kurazume, R & Ohno, E 2020, GAN-Based Method for Synthesizing Multi-focus Cell Images. in JJ Dabrowski, A Rahman & M Paul (eds), Image and Video Technology - PSIVT 2019 International Workshops, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11994 LNCS, Springer, pp. 100-107, 9th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2019, Sydney, オーストラリア, 11/18/19. https://doi.org/10.1007/978-3-030-39770-8_8

Morooka K, Zhang X, Miyauchi S , Kurazume R, Ohno E. GAN-Based Method for Synthesizing Multi-focus Cell Images. In Dabrowski JJ, Rahman A, Paul M, editors, Image and Video Technology - PSIVT 2019 International Workshops, Revised Selected Papers. Springer. 2020. p. 100-107. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-39770-8_8

Morooka, Ken’ich ; Zhang, Xueru ; Miyauchi, Shoko その他. / GAN-Based Method for Synthesizing Multi-focus Cell Images. Image and Video Technology - PSIVT 2019 International Workshops, Revised Selected Papers. editor / Joel Janek Dabrowski ; Ashfaqur Rahman ; Manoranjan Paul. Springer, 2020. pp. 100-107 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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AB - This paper presents a method for synthesizing multi-focus cell images by using generative adversarial networks (GANs). The proposed method, called multi-focus image GAN (MI-GAN), consists of two generators. A base image generator synthesizes a 2D base cell image from random noise. Using the generated base image, a multi-focus cell image generator produces 11 realistic multi-focus images of the cell while considering the relationships between the images acquired at successive focus points. From experimental results, MI-GAN achieves the good performance to generate realistic multi-focus cell images.

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GAN-Based Method for Synthesizing Multi-focus Cell Images

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!!!All Science Journal Classification (ASJC) codes

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