A low noise stenography method for medical images with QR encoding of patient information
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 rec...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2017
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/8953
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/8953
- Palabra clave:
- Codes (symbols)
Health care
Image coding
Image processing
Pixels
Signal encoding
Adjacent pixels
Identification data
Original images
Patient information
Point of interest
Security features
Security methods
Threshold-value
Medical imaging
- Rights
- restrictedAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Cook T.S.Zhang J.Patiño Vanegas, AlbertoContreras Ortiz, Sonia HelenaMartínez-Santos, Juan Carlos2020-03-26T16:32:39Z2020-03-26T16:32:39Z2017Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10138978151060721716057422https://hdl.handle.net/20.500.12585/895310.1117/12.2254568Universidad Tecnológica de BolívarRepositorio UTB571906884595721082285626325154200This 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.Alpinion Medical Systems;The Society of Photo-Optical Instrumentation Engineers (SPIE)Recurso electrónicoapplication/pdfengSPIEhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/restrictedAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_16echttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85020376303&doi=10.1117%2f12.2254568&partnerID=40&md5=3051fea5d265d22297fff383b1f72df0Scopus2-s2.0-85020376303Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and ApplicationsA low noise stenography method for medical images with QR encoding of patient informationinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionConferenciahttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_c94fCodes (symbols)Health careImage codingImage processingPixelsSignal encodingAdjacent pixelsIdentification dataOriginal imagesPatient informationPoint of interestSecurity featuresSecurity methodsThreshold-valueMedical imaging15 February 2017 through 16 February 2017Seenivasagam, V., Velumani, R., A QR code based zero-watermarking scheme for authentication of medical images in teleradiology cloud (2013) Computational and Mathematical Methods in Medicine 2013, , JuneRoek, A., Slavek, K., Dostl, O., Javornk, M., A new approach to fully-reversible watermarking in medical imaging with breakthrough visibility parameters (2016) Biomedical Signal Processing and Control, 29, pp. 44-52Zain, J.M., Fauzi, A.R.M., Aziz, A.A., Clinical evaluation of watermarked medical images (2006) Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE, pp. 5459-5462. , AugWang, Z., Bovik, A.C., A universal image quality index (2002) IEEE Signal Processing Letters, 9, pp. 81-84. , MarchTucker, A., What are those checkerboard things? How qr codes can enrich student projects (2011) Tech Direc-tions, 71 (4), p. 14Rawat, S., Raman, B., A blind watermarking algorithm based on fractional fourier transform and visual cryptography (2012) Signal Processing, 92 (6), pp. 1480-1491http://purl.org/coar/resource_type/c_c94fTHUMBNAILMiniProdInv.pngMiniProdInv.pngimage/png23941https://repositorio.utb.edu.co/bitstream/20.500.12585/8953/1/MiniProdInv.png0cb0f101a8d16897fb46fc914d3d7043MD5120.500.12585/8953oai:repositorio.utb.edu.co:20.500.12585/89532023-05-26 16:29:41.715Repositorio Institucional UTBrepositorioutb@utb.edu.co |
dc.title.none.fl_str_mv |
A low noise stenography method for medical images with QR encoding of patient information |
title |
A low noise stenography method for medical images with QR encoding of patient information |
spellingShingle |
A low noise stenography method for medical images with QR encoding of patient information Codes (symbols) Health care Image coding Image processing Pixels Signal encoding Adjacent pixels Identification data Original images Patient information Point of interest Security features Security methods Threshold-value Medical imaging |
title_short |
A low noise stenography method for medical images with QR encoding of patient information |
title_full |
A low noise stenography method for medical images with QR encoding of patient information |
title_fullStr |
A low noise stenography method for medical images with QR encoding of patient information |
title_full_unstemmed |
A low noise stenography method for medical images with QR encoding of patient information |
title_sort |
A low noise stenography method for medical images with QR encoding of patient information |
dc.contributor.editor.none.fl_str_mv |
Cook T.S. Zhang J. |
dc.subject.keywords.none.fl_str_mv |
Codes (symbols) Health care Image coding Image processing Pixels Signal encoding Adjacent pixels Identification data Original images Patient information Point of interest Security features Security methods Threshold-value Medical imaging |
topic |
Codes (symbols) Health care Image coding Image processing Pixels Signal encoding Adjacent pixels Identification data Original images Patient information Point of interest Security features Security methods Threshold-value Medical imaging |
description |
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. |
publishDate |
2017 |
dc.date.issued.none.fl_str_mv |
2017 |
dc.date.accessioned.none.fl_str_mv |
2020-03-26T16:32:39Z |
dc.date.available.none.fl_str_mv |
2020-03-26T16:32:39Z |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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http://purl.org/coar/resource_type/c_c94f |
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info:eu-repo/semantics/conferenceObject |
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Conferencia |
status_str |
publishedVersion |
dc.identifier.citation.none.fl_str_mv |
Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10138 |
dc.identifier.isbn.none.fl_str_mv |
9781510607217 |
dc.identifier.issn.none.fl_str_mv |
16057422 |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/8953 |
dc.identifier.doi.none.fl_str_mv |
10.1117/12.2254568 |
dc.identifier.instname.none.fl_str_mv |
Universidad Tecnológica de Bolívar |
dc.identifier.reponame.none.fl_str_mv |
Repositorio UTB |
dc.identifier.orcid.none.fl_str_mv |
57190688459 57210822856 26325154200 |
identifier_str_mv |
Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10138 9781510607217 16057422 10.1117/12.2254568 Universidad Tecnológica de Bolívar Repositorio UTB 57190688459 57210822856 26325154200 |
url |
https://hdl.handle.net/20.500.12585/8953 |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.relation.conferencedate.none.fl_str_mv |
15 February 2017 through 16 February 2017 |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_16ec |
dc.rights.uri.none.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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info:eu-repo/semantics/restrictedAccess |
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Atribución-NoComercial 4.0 Internacional |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ Atribución-NoComercial 4.0 Internacional http://purl.org/coar/access_right/c_16ec |
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restrictedAccess |
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Recurso electrónico |
dc.format.mimetype.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
SPIE |
publisher.none.fl_str_mv |
SPIE |
dc.source.none.fl_str_mv |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020376303&doi=10.1117%2f12.2254568&partnerID=40&md5=3051fea5d265d22297fff383b1f72df0 Scopus2-s2.0-85020376303 |
institution |
Universidad Tecnológica de Bolívar |
dc.source.event.none.fl_str_mv |
Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications |
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