Smart markers for watershed-based cell segmentation.

Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand, similar to other image segmentation probl...

Description complète

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Can Fahrettin Koyuncu, Salim Arslan, Irem Durmaz, Rengul Cetin-Atalay, Cigdem Gunduz-Demir
Format:	article
Langue:	EN
Publié:	Public Library of Science (PLoS) 2012
Sujets:	Medicine R Science Q
Accès en ligne:	https://doaj.org/article/5611e020e30a4669942e00a56538e1fb
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

id	oai:doaj.org-article:5611e020e30a4669942e00a56538e1fb
record_format	dspace
spelling	oai:doaj.org-article:5611e020e30a4669942e00a56538e1fb2021-11-18T08:09:09ZSmart markers for watershed-based cell segmentation.1932-620310.1371/journal.pone.0048664https://doaj.org/article/5611e020e30a4669942e00a56538e1fb2012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23152792/?tool=EBIhttps://doaj.org/toc/1932-6203Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand, similar to other image segmentation problems, cell segmentation is an ill-posed problem that typically necessitates the use of domain-specific knowledge to obtain successful segmentations even by human subjects. The approaches that can incorporate this knowledge into their segmentation algorithms have potential to greatly improve segmentation results. In this work, we propose a new approach for the effective segmentation of live cells from phase contrast microscopy. This approach introduces a new set of "smart markers" for a marker-controlled watershed algorithm, for which the identification of its markers is critical. The proposed approach relies on using domain-specific knowledge, in the form of visual characteristics of the cells, to define the markers. We evaluate our approach on a total of 1,954 cells. The experimental results demonstrate that this approach, which uses the proposed definition of smart markers, is quite effective in identifying better markers compared to its counterparts. This will, in turn, be effective in improving the segmentation performance of a marker-controlled watershed algorithm.Can Fahrettin KoyuncuSalim ArslanIrem DurmazRengul Cetin-AtalayCigdem Gunduz-DemirPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 11, p e48664 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Can Fahrettin Koyuncu Salim Arslan Irem Durmaz Rengul Cetin-Atalay Cigdem Gunduz-Demir Smart markers for watershed-based cell segmentation.
description	Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand, similar to other image segmentation problems, cell segmentation is an ill-posed problem that typically necessitates the use of domain-specific knowledge to obtain successful segmentations even by human subjects. The approaches that can incorporate this knowledge into their segmentation algorithms have potential to greatly improve segmentation results. In this work, we propose a new approach for the effective segmentation of live cells from phase contrast microscopy. This approach introduces a new set of "smart markers" for a marker-controlled watershed algorithm, for which the identification of its markers is critical. The proposed approach relies on using domain-specific knowledge, in the form of visual characteristics of the cells, to define the markers. We evaluate our approach on a total of 1,954 cells. The experimental results demonstrate that this approach, which uses the proposed definition of smart markers, is quite effective in identifying better markers compared to its counterparts. This will, in turn, be effective in improving the segmentation performance of a marker-controlled watershed algorithm.
format	article
author	Can Fahrettin Koyuncu Salim Arslan Irem Durmaz Rengul Cetin-Atalay Cigdem Gunduz-Demir
author_facet	Can Fahrettin Koyuncu Salim Arslan Irem Durmaz Rengul Cetin-Atalay Cigdem Gunduz-Demir
author_sort	Can Fahrettin Koyuncu
title	Smart markers for watershed-based cell segmentation.
title_short	Smart markers for watershed-based cell segmentation.
title_full	Smart markers for watershed-based cell segmentation.
title_fullStr	Smart markers for watershed-based cell segmentation.
title_full_unstemmed	Smart markers for watershed-based cell segmentation.
title_sort	smart markers for watershed-based cell segmentation.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/5611e020e30a4669942e00a56538e1fb
work_keys_str_mv	AT canfahrettinkoyuncu smartmarkersforwatershedbasedcellsegmentation AT salimarslan smartmarkersforwatershedbasedcellsegmentation AT iremdurmaz smartmarkersforwatershedbasedcellsegmentation AT rengulcetinatalay smartmarkersforwatershedbasedcellsegmentation AT cigdemgunduzdemir smartmarkersforwatershedbasedcellsegmentation
_version_	1718422167535747072

Smart markers for watershed-based cell segmentation.

Documents similaires