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

Real world robotics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Image and Video Technology - PSIVT 2019 International Workshops, Revised Selected Papers
Editors	Joel Janek Dabrowski, Ashfaqur Rahman, Manoranjan Paul
Publisher	Springer
Pages	100-107
Number of pages	8
ISBN (Print)	9783030397692
DOIs	https://doi.org/10.1007/978-3-030-39770-8_8
Publication status	Published - Jan 1 2020
Event	9th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2019 - Sydney, Australia Duration: Nov 18 2019 → Nov 22 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11994 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	9th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2019
Country/Territory	Australia
City	Sydney
Period	11/18/19 → 11/22/19

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

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

Cite this

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 et al.
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).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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, Australia, 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 et al. / 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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