Interdisciplinary exchange of medical datasets between clinicians and engineers is essential for clinical research. Due to the Data Protection Act, which preserves the rights of patients, full anonymization is necessary before any exchange can take place.
Due to the continuous improvement of image quality of tomographic datasets, anonymization of patient-specific information is not sufficient. In this work, we present a prototype that allows to reliably obscure the facial features of patient data, thus enabling anonymization of neurological datasets in image space.
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Download article PDF. Cite this Share this. Abstract Interdisciplinary exchange of medical datasets between clinicians and engineers is essential for clinical research. Keywords: Anonymization ; Facial Feature Removal. Published Online: Published in Print: This work is licensed under the Creative Commons Attribution 4.
Cite this article. Current Directions in Biomedical Engineering , 7 1 , Current Directions in Biomedical Engineering, Vol. Current Directions in Biomedical Engineering.
