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dc.contributor.authorAbebe, Mekides Assefa
dc.contributor.authorHardeberg, Jon Yngve
dc.contributor.authorVartdal, Gunnar
dc.date.accessioned2022-04-08T06:55:07Z
dc.date.available2022-04-08T06:55:07Z
dc.date.created2022-01-20T22:50:37Z
dc.date.issued2021
dc.identifier.citationJournal of Imaging Science and Technology. 2021, 65 (6), 60407-1-60407-15.en_US
dc.identifier.issn1062-3701
dc.identifier.urihttps://hdl.handle.net/11250/2990636
dc.description.abstractAbstract In recent years, smartphone-based colour imaging systems are being increasingly used for Neonatal jaundice detection applications. These systems are based on the estimation of bilirubin concentration levels that correlates with newborns’ skin colour images corresponding to total serum bilirubin (TSB) and transcutaneous bilirubinometry (TcB) measurements. However, the colour reproduction capacity of smartphone cameras are known to be influenced by various factors including the technological and acquisition process variabilities. To make an accurate bilirubin estimation, irrespective of the type of smartphone and illumination conditions used to capture the newborns’ skin images, an inclusive and complete model, or data set, which can represent all the possible real world acquisitions scenarios needs to be utilized. Due to various challenges in generating such a model or a data set, some solutions tend towards the application of reduced data set (designed for reference conditions and devices only) and colour correction systems (for the transformation of other smartphone skin images to the reference space). Such approaches will make the bilirubin estimation methods highly dependent on the accuracy of their employed colour correction systems, and the capability of reducing device-to-device colour reproduction variability. However, the state-of-the-art methods with similar methodologies were only evaluated and validated on a single smartphone camera. The vulnerability of the systems in making an incorrect jaundice diagnosis can only be shown with a thorough investigation of the colour reproduction variability for extended number of smartphones and illumination conditions. Accordingly, this work presents and discuss the results of such broad investigation, including the evaluation of seven smartphone cameras, ten light sources, and three different colour correction approaches. The overall results show statistically significant colour differences among devices, even after colour correction applications, and that further analysis on clinically significance of such differences is required for skin colour based jaundice diagnosis.en_US
dc.language.isoengen_US
dc.publisherSociety for Imaging Science and Technologyen_US
dc.titleSmartphones’ Skin Colour Reproduction Analysis for Neonatal Jaundice Detectionen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holderThis article will not be available due to copyright restrictions by Society for Imaging Science and Technologyen_US
dc.source.pagenumber60407-1-60407-15en_US
dc.source.volume65en_US
dc.source.journalJournal of Imaging Science and Technologyen_US
dc.source.issue6en_US
dc.identifier.doihttps://doi.org/10.2352/J.ImagingSci.Technol.2021.65.6.060407
dc.identifier.cristin1986987
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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