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

Affiliation: University of Kent, United Kingdom

ISBN: 978-989-758-215-8

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

Related Ontology Subjects/Areas/Topics: Bioimaging ; Biomedical Engineering ; Conventional Microscopy ; Quantitative Bioimaging

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 - Segmenting Cells from Light Microscopy Images.In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2 BIOIMAGING: BIOIMAGING, (BIOSTEC 2017) ISBN 978-989-758-215-8, 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 - Segmenting Cells from Light Microscopy Images},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2 BIOIMAGING: BIOIMAGING, (BIOSTEC 2017)},
year={2017},
pages={92-99},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006149100920099},
isbn={978-989-758-215-8},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2 BIOIMAGING: BIOIMAGING, (BIOSTEC 2017)
TI - Automated Cell Segmentation of Fission Yeast Phase Images - Segmenting Cells from Light Microscopy Images
SN - 978-989-758-215-8
AU - O'Brien, J.
AU - Hoque, S.
AU - Mulvihill, D.
AU - Sirlantzis, K.
PY - 2017
SP - 92
EP - 99
DO - 10.5220/0006149100920099

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