GAN-Based Method for Synthesizing Multi-focus Cell Images

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

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

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
出版ステータス出版済み - 1 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 18 201911 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)
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
CitySydney
Period11/18/1911/22/19

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(全般)

フィンガープリント

「GAN-Based Method for Synthesizing Multi-focus Cell Images」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル