Cell segmentation methods for label-free contrast microscopy: review and comprehensive comparison

dc.contributor.authorVičar, Tomášcs
dc.contributor.authorBalvan, Jancs
dc.contributor.authorJaroš, Josefcs
dc.contributor.authorJug, Floriancs
dc.contributor.authorKolář, Radimcs
dc.contributor.authorMasařík, Michalcs
dc.contributor.authorGumulec, Jaromírcs
dc.coverage.issue1cs
dc.coverage.volume20cs
dc.date.issued2019-07-28cs
dc.description.abstractBecause of its non-destructive nature, label-free imaging is an important strategy for studying biological processes. However, routine microscopic techniques like phase contrast or DIC suffer from shadow-cast artifacts making automatic segmentation challenging. The aim of this study was to compare the segmentation efficacy of published steps of segmentation work-flow (image reconstruction, foreground segmentation, cell detection (seed-point extraction) and cell (instance) segmentation) on a dataset of the same cells from multiple contrast microscopic modalities.en
dc.description.abstractBecause of its non-destructive nature, label-free imaging is an important strategy for studying biological processes. However, routine microscopic techniques like phase contrast or DIC suffer from shadow-cast artifacts making automatic segmentation challenging. The aim of this study was to compare the segmentation efficacy of published steps of segmentation work-flow (image reconstruction, foreground segmentation, cell detection (seed-point extraction) and cell (instance) segmentation) on a dataset of the same cells from multiple contrast microscopic modalities.en
dc.formattextcs
dc.format.extent1-25cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationBMC BIOINFORMATICS. 2019, vol. 20, issue 1, p. 1-25.en
dc.identifier.doi10.1186/s12859-019-2880-8cs
dc.identifier.issn1471-2105cs
dc.identifier.orcid0000-0002-9136-7873cs
dc.identifier.orcid0000-0002-0469-6397cs
dc.identifier.orcid0000-0003-1172-7195cs
dc.identifier.orcid0000-0002-9658-3444cs
dc.identifier.other158175cs
dc.identifier.researcheridC-6006-2018cs
dc.identifier.researcheridC-8547-2014cs
dc.identifier.researcheridD-9920-2012cs
dc.identifier.researcheridD-7638-2012cs
dc.identifier.scopus57202426072cs
dc.identifier.scopus55769747816cs
dc.identifier.urihttp://hdl.handle.net/11012/195836
dc.language.isoencs
dc.publisherBMCcs
dc.relation.ispartofBMC BIOINFORMATICScs
dc.relation.urihttps://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2880-8cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1471-2105/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectMicroscopyen
dc.subjectCell segmentationen
dc.subjectImage reconstructionen
dc.subjectMethods comparisonen
dc.subjectDifferential contrast imageen
dc.subjectQuantitative phase imagingen
dc.subjectLaplacian of Gaussiansen
dc.subjectMicroscopy
dc.subjectCell segmentation
dc.subjectImage reconstruction
dc.subjectMethods comparison
dc.subjectDifferential contrast image
dc.subjectQuantitative phase imaging
dc.subjectLaplacian of Gaussians
dc.titleCell segmentation methods for label-free contrast microscopy: review and comprehensive comparisonen
dc.title.alternativeCell segmentation methods for label-free contrast microscopy: review and comprehensive comparisonen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-158175en
sync.item.dbtypeVAVen
sync.item.insts2025.10.14 14:08:58en
sync.item.modts2025.10.14 09:47:42en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav biomedicínského inženýrstvícs
thesis.grantorVysoké učení technické v Brně. Středoevropský technologický institut VUT. Energie budoucnosti a inovacecs

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