Automated Cell Segmentation of Fission Yeast Phase Images

Jennifer O; Sanaul Hoque; Daniel Mulvihill; Konstantinos Sirlantzis

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Paper

Automated Cell Segmentation of Fission Yeast Phase Images

Topics: Conventional Microscopy; Quantitative Bioimaging

In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOSTEC, 92-99, 2017 , Porto, Portugal

Authors: Jennifer O'Brien ; Sanaul Hoque ; Daniel Mulvihill and Konstantinos Sirlantzis

Affiliation: University of Kent, United Kingdom

Keyword(s): Automated Segmentation, Light Microscopy, Fission Yeast.

Abstract: Robust image analysis is an important aspect of all cell biology studies. The geometrics of cells are critical for developing an understanding of biological processes. Time constraints placed on researchers lead to a narrower focus on what data are collected and recorded from an experiment, resulting in a loss of data. Currently, preprocessing of microscope images is followed by the utilisation and parameterisation of inbuilt functions of various softwares to obtain information. Using the fission yeast, Schizosaccharomyes pombe, we propose a novel, fully automated, segmentation software for cells with a significantly lower rate of segmentation errors than PombeX with the same dataset.

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Paper citation in several formats:

O'Brien, J.; Hoque, S.; Mulvihill, D. and Sirlantzis, K. (2017). Automated Cell Segmentation of Fission Yeast Phase Images. In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - BIOIMAGING; ISBN 978-989-758-215-8; ISSN 2184-4305, SciTePress, pages 92-99. DOI: 10.5220/0006149100920099

@conference{bioimaging17,
author={Jennifer O'Brien. and Sanaul Hoque. and Daniel Mulvihill. and Konstantinos Sirlantzis.},
title={Automated Cell Segmentation of Fission Yeast Phase Images},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - BIOIMAGING},
year={2017},
pages={92-99},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006149100920099},
isbn={978-989-758-215-8},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - BIOIMAGING
TI - Automated Cell Segmentation of Fission Yeast Phase Images
SN - 978-989-758-215-8
IS - 2184-4305
AU - O'Brien, J.
AU - Hoque, S.
AU - Mulvihill, D.
AU - Sirlantzis, K.
PY - 2017
SP - 92
EP - 99
DO - 10.5220/0006149100920099
PB - SciTePress