dc.contributorCook T.S.
dc.contributorZhang J.
dc.creatorPatiño Vanegas, Alberto
dc.creatorContreras Ortiz, Sonia Helena
dc.creatorMartínez-Santos, Juan Carlos
dc.date.accessioned2020-03-26T16:32:39Z
dc.date.available2020-03-26T16:32:39Z
dc.date.created2020-03-26T16:32:39Z
dc.date.issued2017
dc.identifierProgress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10138
dc.identifier9781510607217
dc.identifier16057422
dc.identifierhttps://hdl.handle.net/20.500.12585/8953
dc.identifier10.1117/12.2254568
dc.identifierUniversidad Tecnológica de Bolívar
dc.identifierRepositorio UTB
dc.identifier57190688459
dc.identifier57210822856
dc.identifier26325154200
dc.description.abstractThis paper proposes an approach to facilitate the process of individualization of patients from their medical images, without compromising the inherent confidentiality of medical data. The identification of a patient from a medical image is not often the goal of security methods applied to image records. Usually, any identification data is removed from shared records, and security features are applied to determine ownership. We propose a method for embedding a QR-code containing information that can be used to individualize a patient. This is done so that the image to be shared does not differ significantly from the original image. The QR-code is distributed in the image by changing several pixels according to a threshold value based on the average value of adjacent pixels surrounding the point of interest. The results show that the code can be embedded and later fully recovered with minimal changes in the UIQI index - less than 0.1% of different. © 2017 SPIE.
dc.languageeng
dc.publisherSPIE
dc.relation15 February 2017 through 16 February 2017
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.rightsAtribución-NoComercial 4.0 Internacional
dc.sourcehttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85020376303&doi=10.1117%2f12.2254568&partnerID=40&md5=3051fea5d265d22297fff383b1f72df0
dc.sourceScopus2-s2.0-85020376303
dc.sourceMedical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications
dc.titleA low noise stenography method for medical images with QR encoding of patient information


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