| Facial Recognition Software Success Rates for the Identification of 3D Surface Reconstructed Facial Images: Implications for Patient Privacy and Security. | |
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MedLine Citation:
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PMID: 22065158 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Image de-identification has focused on the removal of textual protected health information (PHI). Surface reconstructions of the face have the potential to reveal a subject's identity even when textual PHI is absent. This study assessed the ability of a computer application to match research subjects' 3D facial reconstructions with conventional photographs of their face. In a prospective study, 29 subjects underwent CT scans of the head and had frontal digital photographs of their face taken. Facial reconstructions of each CT dataset were generated on a 3D workstation. In phase 1, photographs of the 29 subjects undergoing CT scans were added to a digital directory and tested for recognition using facial recognition software. In phases 2-4, additional photographs were added in groups of 50 to increase the pool of possible matches and the test for recognition was repeated. As an internal control, photographs of all subjects were tested for recognition against an identical photograph. Of 3D reconstructions, 27.5% were matched correctly to corresponding photographs (95% upper CL, 40.1%). All study subject photographs were matched correctly to identical photographs (95% lower CL, 88.6%). Of 3D reconstructions, 96.6% were recognized simply as a face by the software (95% lower CL, 83.5%). Facial recognition software has the potential to recognize features on 3D CT surface reconstructions and match these with photographs, with implications for PHI. |
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Authors:
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Jan C Mazura; Krishna Juluru; Joseph J Chen; Tara A Morgan; Majnu John; Eliot L Siegel |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-11-8 |
Journal Detail:
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Title: Journal of digital imaging : the official journal of the Society for Computer Applications in Radiology Volume: - ISSN: 1618-727X ISO Abbreviation: - Publication Date: 2011 Nov |
Date Detail:
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Created Date: 2011-11-8 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9100529 Medline TA: J Digit Imaging Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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Department of Radiology, Weill Cornell Medical College, 525 E 68th St, F-056, New York, NY, 10065, USA, jmazura@gmail.com. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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