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dc.contributor.authorMilosevic, Vladan
dc.date.accessioned2024-01-02T14:14:07Z
dc.date.available2024-01-02T14:14:07Z
dc.date.created2023-06-23T10:17:42Z
dc.date.issued2023
dc.identifier.issn2635-0041
dc.identifier.urihttps://hdl.handle.net/11250/3109389
dc.description.abstractImaging Mass Cytometry (IMC) is a novel, high multiplexing imaging platform capable of simultaneously detecting and visualizing up to 40 different protein targets. It is a strong asset available for in-depth study of histology and pathophysiology of the tissues. Bearing in mind the robustness of this technique and the high spatial context of the data it gives, it is especially valuable in studying the biology of cancer and tumor microenvironment. IMC-derived data are not classical micrographic images, and due to the characteristics of the data obtained using IMC, the image analysis approach, in this case, can diverge to a certain degree from the classical image analysis pipelines. As the number of publications based on the IMC is on the rise, this trend is also followed by an increase in the number of available methodologies designated solely to IMC-derived data analysis. This review has for an aim to give a systematic synopsis of all the available classical image analysis tools and pipelines useful to be employed for IMC data analysis and give an overview of tools intentionally developed solely for this purpose, easing the choice to researchers of selecting the most suitable methodologies for a specific type of analysis desired.en_US
dc.language.isoengen_US
dc.publisherOxford University Pressen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleDifferent approaches to Imaging Mass Cytometry data analysisen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2023 The Author(s)en_US
dc.source.articlenumbervbad046en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.doi10.1093/bioadv/vbad046
dc.identifier.cristin2157342
dc.source.journalBioinformatics Advancesen_US
dc.identifier.citationBioinformatics Advances. 2023, 3 (1), vbad046.en_US
dc.source.volume3en_US
dc.source.issue1en_US


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