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dc.contributor.authorSomani, Ayush
dc.contributor.authorSekh, Arif Ahmed
dc.contributor.authorOpstad, Ida Sundvor
dc.contributor.authorBirgisdottir, Åsa birna
dc.contributor.authorMyrmel, Truls
dc.contributor.authorAhluwalia, Balpreet Singh
dc.contributor.authorHorsch, Alexander
dc.contributor.authorAgarwal, Krishna
dc.contributor.authorPrasad, Dilip K.
dc.date.accessioned2023-01-10T12:24:24Z
dc.date.available2023-01-10T12:24:24Z
dc.date.issued2022-09-28
dc.description.abstractMitochondria play a crucial role in cellular metabolism. This paper presents a novel method to visualize mitochondria in living cells without the use of fluorescent markers. We propose a physics-guided deep learning approach for obtaining virtually labeled micrographs of mitochondria from bright-field images. We integrate a microscope’s point spread function in the learning of an adversarial neural network for improving virtual labeling. We show results (average Pearson correlation 0.86) significantly better than what was achieved by state-of-the-art (0.71) for virtual labeling of mitochondria. We also provide new insights into the virtual labeling problem and suggest additional metrics for quality assessment. The results show that our virtual labeling approach is a powerful way of segmenting and tracking individual mitochondria in bright-field images, results previously achievable only for fluorescently labeled mitochondria.en_US
dc.identifier.citationSomani, Sekh, Opstad, Birgisdottir, Myrmel, Ahluwalia, Horsch, Agarwal, Prasad. Virtual labeling of mitochondria in living cells using correlative imaging and physics-guided deep learning. Biomedical Optics Express. 2022;13(10):5495-5516en_US
dc.identifier.cristinIDFRIDAID 2094929
dc.identifier.doi10.1364/BOE.464177
dc.identifier.issn2156-7085
dc.identifier.urihttps://hdl.handle.net/10037/28124
dc.language.isoengen_US
dc.publisherOptica Publishing Groupen_US
dc.relation.journalBiomedical Optics Express
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/964800/EU/Technology for real-time visualizing and modelling of fundamental process in living organoids towards new insights into organ-specific health, disease, and recovery/OrganVision/en_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/804233/EU/Label-free 3D morphological nanoscopy for studying sub-cellular dynamics in live cancer cells with high spatio-temporal resolution/3D-nanoMorph/en_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2022 Optica Publishing Groupen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)en_US
dc.titleVirtual labeling of mitochondria in living cells using correlative imaging and physics-guided deep learningen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)