Automated Cell Segmentation in Phase-Contrast Images based on
Classification and Region Growing

D 2015

Automated Cell Segmentation in Phase-Contrast Images based on Classification and Region Growing

STOKLASA, Roman, Lukáš BÁLEK, Pavel KREJČÍ a Petr MATULA

Základní údaje

Originální název

Automated Cell Segmentation in Phase-Contrast Images based on Classification and Region Growing

Autoři

STOKLASA, Roman (703 Slovensko, domácí), Lukáš BÁLEK (203 Česká republika, domácí), Pavel KREJČÍ (203 Česká republika, domácí) a Petr MATULA (203 Česká republika, garant, domácí)

Vydání

Neuveden, Proceedings of 2015 IEEE International Symposium on Biomedical Imaging, 2015. od s. 1447-1451, 5 s. 2015

Nakladatel

Engineering in Medicine and Biology Society

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

20200 2.2 Electrical engineering, Electronic engineering, Information engineering

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

paměťový nosič (CD, DVD, flash disk)

Odkazy

URL

Kód RIV

RIV/00216224:14330/15:00082559

Organizační jednotka

Fakulta informatiky

ISBN

978-1-4799-2374-8

ISSN

DOI

http://dx.doi.org/10.1109/ISBI.2015.7164149

UT WoS

000380546000348

Klíčová slova anglicky

phase-contrast microscopy; segmentation; classification; superpixel; cells

Štítky

best2, cbia-web, firank_B

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 26. 6. 2020 10:45, Mgr. Marie Šípková, DiS.

Anotace

V originále

Cell segmentation in phase-contrast microscopy images remains a challenging problem because of the large variability in subcellular structures and imaging artifacts. In this paper, we present an approach to the automatic segmentation of tightly packed cells in phase-contrast images. We combine the classification of superpixels with the region-growing method to locate cell membrane boundaries. We demonstrate that such a combined approach is able to perform the task of cell detection and segmentation with a high level of precision. On the presented dataset, we achieved 90% precision with 78% recall. The results indicate that this method is suitable for real biological applications.

Návaznosti

MUNI/A/1159/2014, interní kód MU

Název: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace IV.

Investor: Masarykova univerzita, Rozsáhlé výpočetní systémy: modely, aplikace a verifikace IV., DO R. 2020_Kategorie A - Specifický výzkum - Studentské výzkumné projekty

MUNI/A/1206/2014, interní kód MU

Název: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity (Akronym: SKOMU)

Investor: Masarykova univerzita, Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity, DO R. 2020_Kategorie A - Specifický výzkum - Studentské výzkumné projekty

MUNI/M/0071/2013, interní kód MU

Název: High-throughput screening of compound libraries aimed on discovery of novel inhibitors of the FGFR/ERK MAP kinase signaling (Akronym: HTS-FGFR)

Investor: Masarykova univerzita, High-throughput screening of compound libraries aimed on discovery of novel inhibitors of the FGFR/ERK MAP kinase signaling, INTERDISCIPLINARY - Mezioborové výzkumné projekty

Citovat

STOKLASA, Roman, Lukáš BÁLEK, Pavel KREJČÍ a Petr MATULA. Automated Cell Segmentation in Phase-Contrast Images based on Classification and Region Growing. In Proceedings of 2015 IEEE International Symposium on Biomedical Imaging, 2015. Neuveden: Engineering in Medicine and Biology Society, 2015, s. 1447-1451. ISBN 978-1-4799-2374-8. Dostupné z: https://dx.doi.org/10.1109/ISBI.2015.7164149.

@inproceedings{1230987,
   author = {Stoklasa, Roman and Bálek, Lukáš and Krejčí, Pavel and Matula, Petr},
   address = {Neuveden},
   booktitle = {Proceedings of 2015 IEEE International Symposium on Biomedical Imaging, 2015.},
   doi = {http://dx.doi.org/10.1109/ISBI.2015.7164149},
   keywords = {phase-contrast microscopy; segmentation; classification; superpixel; cells},
   howpublished = {paměťový nosič},
   language = {eng},
   location = {Neuveden},
   isbn = {978-1-4799-2374-8},
   pages = {1447-1451},
   publisher = {Engineering in Medicine and Biology Society},
   title = {Automated Cell Segmentation in Phase-Contrast Images based on Classification and Region Growing},
   url = {https://ieeexplore.ieee.org/document/7164149},
   year = {2015}
}

TY  - JOUR
ID  - 1230987
AU  - Stoklasa, Roman - Bálek, Lukáš - Krejčí, Pavel - Matula, Petr
PY  - 2015
TI  - Automated Cell Segmentation in Phase-Contrast Images based on Classification and Region Growing
PB  - Engineering in Medicine and Biology Society
CY  - Neuveden
SN  - 9781479923748
KW  - phase-contrast microscopy
KW  - segmentation
KW  - classification
KW  - superpixel
KW  - cells
UR  - https://ieeexplore.ieee.org/document/7164149
L2  - https://ieeexplore.ieee.org/document/7164149
N2  - Cell segmentation in phase-contrast microscopy images remains a challenging problem because of the large variability in subcellular structures and imaging artifacts. In this paper, we present an approach to the automatic segmentation of tightly packed cells in phase-contrast images. We combine the classification of superpixels with the region-growing method to locate cell membrane boundaries. We demonstrate that such a combined approach is able to perform the task of cell detection and segmentation with a high level of precision. On the presented dataset, we achieved 90% precision with 78% recall. The results indicate that this method is suitable for real biological applications.
ER  -

STOKLASA, Roman, Lukáš BÁLEK, Pavel KREJČÍ a Petr MATULA. Automated Cell Segmentation in Phase-Contrast Images based on Classification and Region Growing. In \textit{Proceedings of 2015 IEEE International Symposium on Biomedical Imaging, 2015.}. Neuveden: Engineering in Medicine and Biology Society, 2015, s.~1447-1451. ISBN~978-1-4799-2374-8. Dostupné z: https://dx.doi.org/10.1109/ISBI.2015.7164149.

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