Facing privacy in neuroimaging: removing facial features degrades performance of image analysis methods
Academic Article
Publication Date:
2020
Short description:
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., Filippi, M., Enzinger, C., Frederiksen, J., Ciccarelli, O., Guttmann, C.R.G., Wattjes, M.P., Witte, M.G., de Witt Hamer, P.C., Barkhof, F., Vrenken, H., et al.. - In: EUROPEAN RADIOLOGY. - ISSN 0938-7994. - 30:(2020), pp. 1062-1074. [10.1007/s00330-019-06459-3]
abstract:
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.
Iris type:
1.1 Articolo in rivista
Keywords:
Database; Ethics; Magnetic resonance imaging; Neuroimaging; Privacy
List of contributors:
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; Filippi, M; Enzinger, C; Frederiksen, J; Ciccarelli, O; Guttmann, C R G; Wattjes, M P; Witte, M G; de Witt Hamer, P C; Barkhof, F; Vrenken, H; MAGNIMS Study Group and Alzheimer’s Disease Neuroimaging, Initiative; Rocca, M. A.
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