Segmentation of Cell Membrane and Nucleus by Improving Pix2pix
Masaya Sato, Kazuhiro Hotta, Ayako Imanishi, Michiyuki Matsuda, Kenta Terai
2018
Abstract
We propose a semantic segmentation method of cell membrane and nucleus by improving pix2pix. We use pix2pix which is an improved method of DCGAN. Pix2pix generates good segmentation result by the competition of generator and discriminator but pix2pix uses generator and discriminator independently. If generator knows the criterion for classifying real and fake images, we can improve the accuracy of generator furthermore. Thus, we propose to use the feature maps of the discriminator into generator. In experiments on segmentation of cell membrane and nucleus, our proposed method outperformed the conventional pix2pix.
DownloadPaper Citation
in Harvard Style
Sato M., Hotta K., Imanishi A., Matsuda M. and Terai K. (2018). Segmentation of Cell Membrane and Nucleus by Improving Pix2pix. In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - Volume 4: BIOSIGNALS; ISBN 978-989-758-279-0, SciTePress, pages 216-220. DOI: 10.5220/0006648302160220
in Bibtex Style
@conference{biosignals18,
author={Masaya Sato and Kazuhiro Hotta and Ayako Imanishi and Michiyuki Matsuda and Kenta Terai},
title={Segmentation of Cell Membrane and Nucleus by Improving Pix2pix},
booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - Volume 4: BIOSIGNALS},
year={2018},
pages={216-220},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006648302160220},
isbn={978-989-758-279-0},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - Volume 4: BIOSIGNALS
TI - Segmentation of Cell Membrane and Nucleus by Improving Pix2pix
SN - 978-989-758-279-0
AU - Sato M.
AU - Hotta K.
AU - Imanishi A.
AU - Matsuda M.
AU - Terai K.
PY - 2018
SP - 216
EP - 220
DO - 10.5220/0006648302160220
PB - SciTePress