most citedDeep Learning-based Anonymization of Chest Radiographs: A Utility-preserving Measure for Patient Privacy

3 citations · 3 across the 1 of their papers we have counts for

collaborators

2 papers

eess.IV2022★ 3 cited

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…

cs.CV2021

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…