Yayın:
Automated Analysis of Wound Healing Microscopy Image Series - A Preliminary Study

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dc.contributor.authorMayalive, Berkay
dc.contributor.authorSaylig, Orkun
dc.contributor.authorOzuysal, Ozden Y.
dc.contributor.authorOkvur, Devrim P.
dc.contributor.authorToreyin, Behcet Ugur
dc.contributor.authorUnay, Devrim
dc.contributor.ituauthorTöreyin, Behçet Uğur
dc.date.accessioned2026-01-29T05:52:02Z
dc.date.issued2020-11-19
dc.description.abstractCollective cell analysis from microscopy image series is important for wound healing research. Computer-based automation of such analyses may help in rapid acquisition of reliable and reproducible results. In this study phase-contrast optical microscopy image series of an in-vitro wound healing essay is manually delineated by two experts and its analysis is realized, traditional image processing and deep learning based approaches for automated segmentation of wound area are developed and their performance comparisons are carried out.
dc.description.urihttps://doi.org/10.1109/tiptekno50054.2020.9299213
dc.description.urihttps://dx.doi.org/10.1109/tiptekno50054.2020.9299213
dc.identifier.doi10.1109/tiptekno50054.2020.9299213
dc.identifier.endpage4
dc.identifier.openairedoi_dedup___::913342fe39c0f41940ef5be8aeed2cb9
dc.identifier.orcid0000-0001-8333-4193
dc.identifier.orcid0000-0003-4406-2783
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/11527/68264
dc.publisherIEEE
dc.relation.ispartof2020 Medical Technologies Congress (TIPTEKNO)
dc.rightsCLOSED
dc.titleAutomated Analysis of Wound Healing Microscopy Image Series - A Preliminary Study
dc.typeArticle
dspace.entity.typePublication
person.identifier.orcid0000-0003-4406-2783

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