2 citations · 6 across the 4 of their papers we have counts for
11 papers
Conditional De-Identification of 3D Magnetic Resonance Images
Lennart Alexander Van der Goten, Tobias Hepp, Zeynep Akata +1
Privacy protection of medical image data is challenging. Even if metadata is removed, brain scans are vulnerable to attacks that match renderings of the face to facial image databa…
Uncertainty-Guided Progressive GANs for Medical Image Translation
Uddeshya Upadhyay, Yanbei Chen, Tobias Hepp +2
Image-to-image translation plays a vital role in tackling various medical imaging tasks such as attenuation correction, motion correction, undersampled reconstruction, and denoisin…
Uncertainty-Based Biological Age Estimation of Brain MRI Scans
Karim Armanious, Sherif Abdulatif, Wenbin Shi +3
Age is an essential factor in modern diagnostic procedures. However, assessment of the true biological age (BA) remains a daunting task due to the lack of reference ground-truth la…
Overcoming Barriers to Data Sharing with Medical Image Generation: A Comprehensive Evaluation
August DuMont Schütte, Jürgen Hetzel, Sergios Gatidis +4
Privacy concerns around sharing personally identifiable information are a major practical barrier to data sharing in medical research. However, in many cases, researchers have no i…
Age-Net: An MRI-Based Iterative Framework for Brain Biological Age Estimation
Karim Armanious, Sherif Abdulatif, Wenbin Shi +6
The concept of biological age (BA), although important in clinical practice, is hard to grasp mainly due to the lack of a clearly defined reference standard. For specific applicati…
Fully Automated and Standardized Segmentation of Adipose Tissue Compartments by Deep Learning in Three-dimensional Whole-body MRI of Epidemiological Cohort Studies
Thomas Küstner, Tobias Hepp, Marc Fischer +9
Purpose: To enable fast and reliable assessment of subcutaneous and visceral adipose tissue compartments derived from whole-body MRI. Methods: Quantification and localization of di…