90 citations · 111 across the 3 of their papers we have counts for
3 papers
The Impact of Speech Anonymization on Pathology and Its Limits
Soroosh Tayebi Arasteh, Tomas Arias-Vergara, Paula Andrea Perez-Toro +6
Integration of speech into healthcare has intensified privacy concerns due to its potential as a non-invasive biomarker containing individual biometric information. In response, sp…
Deep Learning-based Anonymization of Chest Radiographs: A Utility-preserving Measure for Patient Privacy
Kai Packhäuser, Sebastian Gündel, Florian Thamm +2
Robust and reliable anonymization of chest radiographs constitutes an essential step before publishing large datasets of such for research purposes. The conventional anonymization…
Deep Learning-based Patient Re-identification Is able to Exploit the Biometric Nature of Medical Chest X-ray Data
Kai Packhäuser, Sebastian Gündel, Nicolas Münster +3
With the rise and ever-increasing potential of deep learning techniques in recent years, publicly available medical datasets became a key factor to enable reproducible development…