publication . Article . Other literature type . 2020

Facing privacy in neuroimaging: removing facial features degrades performance of image analysis methods

de Sitter, A.; Visser, M.; Brouwer, I.; Cover, K. S.; van Schijndel, R. A.; Eijgelaar, R. S.; Müller, D. M. J.; Ropele, S.; Kappos, L.; Rovira, Á.; ...
Open Access English
  • Published: 01 Feb 2020
Background Recent studies have created awareness that facial features can be reconstructed from high-resolution MRI. Therefore, data sharing in neuroimaging requires special attention to protect participants’ privacy. Facial features removal (FFR) could alleviate these concerns. We assessed the impact of three FFR methods on subsequent automated image analysis to obtain clinically relevant outcome measurements in three clinical groups. Methods FFR was performed using QuickShear, FaceMasking, and Defacing. In 110 subjects of Alzheimer’s Disease Neuroimaging Initiative, normalized brain volumes (NBV) were measured by SIENAX. In 70 multiple sclerosis patients of th...
free text keywords: /dk/atira/pure/researchoutput/pubmedpublicationtype/D016428, Journal Article, Database, Ethics, Magnetic resonance imaging, Neuroimaging, Privacy, Radiology Nuclear Medicine and imaging, yes, Magnetic Resonance
Funded by
NIH| Alzheimers Disease Neuroimaging Initiative
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1U01AG024904-01
  • Funder: Canadian Institutes of Health Research (CIHR)

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