dc.contributor | Cook T.S. | |
dc.contributor | Zhang J. | |
dc.creator | Patiño Vanegas, Alberto | |
dc.creator | Contreras Ortiz, Sonia Helena | |
dc.creator | Martínez-Santos, Juan Carlos | |
dc.date.accessioned | 2020-03-26T16:32:39Z | |
dc.date.available | 2020-03-26T16:32:39Z | |
dc.date.created | 2020-03-26T16:32:39Z | |
dc.date.issued | 2017 | |
dc.identifier | Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10138 | |
dc.identifier | 9781510607217 | |
dc.identifier | 16057422 | |
dc.identifier | https://hdl.handle.net/20.500.12585/8953 | |
dc.identifier | 10.1117/12.2254568 | |
dc.identifier | Universidad Tecnológica de Bolívar | |
dc.identifier | Repositorio UTB | |
dc.identifier | 57190688459 | |
dc.identifier | 57210822856 | |
dc.identifier | 26325154200 | |
dc.description.abstract | This 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.language | eng | |
dc.publisher | SPIE | |
dc.relation | 15 February 2017 through 16 February 2017 | |
dc.rights | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.rights | info:eu-repo/semantics/restrictedAccess | |
dc.rights | Atribución-NoComercial 4.0 Internacional | |
dc.source | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020376303&doi=10.1117%2f12.2254568&partnerID=40&md5=3051fea5d265d22297fff383b1f72df0 | |
dc.source | Scopus2-s2.0-85020376303 | |
dc.source | Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications | |
dc.title | A low noise stenography method for medical images with QR encoding of patient information | |