A DICOM dataset for evaluation of medical image de-identification

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dc.contributor.authorRutherford, Michaelen
dc.contributor.authorMun, Seong K.en
dc.contributor.authorLevine, Bettyen
dc.contributor.authorBennett, Williamen
dc.contributor.authorSmith, Kirken
dc.contributor.authorFarmer, Philen
dc.contributor.authorJarosz, Quasaren
dc.contributor.authorWagner, Ulrikeen
dc.contributor.authorFreyman, Johnen
dc.contributor.authorBlake, Gerien
dc.contributor.authorTarbox, Lawrenceen
dc.contributor.authorFarahani, Keyvanen
dc.contributor.authorPrior, Freden
dc.date.accessioned2022-04-08T13:06:44Zen
dc.date.available2022-04-08T13:06:44Zen
dc.date.issued2021-07-16en
dc.description.abstractWe developed a DICOM dataset that can be used to evaluate the performance of de-identification algorithms. DICOM objects (a total of 1,693 CT, MRI, PET, and digital X-ray images) were selected from datasets published in the Cancer Imaging Archive (TCIA). Synthetic Protected Health Information (PHI) was generated and inserted into selected DICOM Attributes to mimic typical clinical imaging exams. The DICOM Standard and TCIA curation audit logs guided the insertion of synthetic PHI into standard and non-standard DICOM data elements. A TCIA curation team tested the utility of the evaluation dataset. With this publication, the evaluation dataset (containing synthetic PHI) and de-identified evaluation dataset (the result of TCIA curation) are released on TCIA in advance of a competition, sponsored by the National Cancer Institute (NCI), for algorithmic de-identification of medical image datasets. The competition will use a much larger evaluation dataset constructed in the same manner. This paper describes the creation of the evaluation datasets and guidelines for their use.en
dc.description.notesThis project has been funded in whole or in part with federal funds from the National Cancer Institute, Contract No. 75N91019D00024, Subcontract 20X023F. Funding for Posda development is provided by U24CA215109. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.en
dc.description.sponsorshipNational Cancer InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Cancer Institute (NCI) [75N91019D00024, 20X023F, U24CA215109]en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1038/s41597-021-00967-yen
dc.identifier.eissn2052-4463en
dc.identifier.issue1en
dc.identifier.other183en
dc.identifier.pmid34272388en
dc.identifier.urihttp://hdl.handle.net/10919/109609en
dc.identifier.volume8en
dc.language.isoenen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleA DICOM dataset for evaluation of medical image de-identificationen
dc.title.serialScientific Dataen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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