599 citations · 700 across the 10 of their papers we have counts for
12 papers
Adapted Foundation Models for Breast MRI Triaging in Contrast-Enhanced and Non-Contrast Enhanced Protocols
Tri-Thien Nguyen, Lorenz A. Kapsner, Tobias Hepp +13
Background: Magnetic resonance imaging (MRI) has high sensitivity for breast cancer detection, but interpretation is time-consuming. Artificial intelligence may aid in pre-screenin…
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…
ipA-MedGAN: Inpainting of Arbitrary Regions in Medical Imaging
Karim Armanious, Vijeth Kumar, Sherif Abdulatif +3
Local deformations in medical modalities are common phenomena due to a multitude of factors such as metallic implants or limited field of views in magnetic resonance imaging (MRI).…
Organ-based Chronological Age Estimation based on 3D MRI Scans
Karim Armanious, Sherif Abdulatif, Anish Rao Bhaktharaguttu +4
Individuals age differently depending on a multitude of different factors such as lifestyle, medical history and genetics. Often, the global chronological age is not indicative of…
MedGAN: Medical Image Translation using GANs
Karim Armanious, Chenming Jiang, Marc Fischer +4
Image-to-image translation is considered a new frontier in the field of medical image analysis, with numerous potential applications. However, a large portion of recent approaches…
An update on statistical boosting in biomedicine
Andreas Mayr, Benjamin Hofner, Elisabeth Waldmann +3
Statistical boosting algorithms have triggered a lot of research during the last decade. They combine a powerful machine-learning approach with classical statistical modelling, off…
Probing for sparse and fast variable selection with model-based boosting
Janek Thomas, Tobias Hepp, Andreas Mayr +1
We present a new variable selection method based on model-based gradient boosting and randomly permuted variables. Model-based boosting is a tool to fit a statistical model while p…