3 citations · 13 across the 30 of their papers we have counts for
7 papers · 1 filter
Estimating Neural Orientation Distribution Fields on High Resolution Diffusion MRI Scans
Mohammed Munzer Dwedari, William Consagra, Philip Müller +3
The Orientation Distribution Function (ODF) characterizes key brain microstructural properties and plays an important role in understanding brain structural connectivity. Recent wo…
Diffusion-based Generative Image Outpainting for Recovery of FOV-Truncated CT Images
Michelle Espranita Liman, Daniel Rueckert, Florian J. Fintelmann +1
Field-of-view (FOV) recovery of truncated chest CT scans is crucial for accurate body composition analysis, which involves quantifying skeletal muscle and subcutaneous adipose tiss…
Diff-Def: Diffusion-Generated Deformation Fields for Conditional Atlases
Sophie Starck, Vasiliki Sideri-Lampretsa, Bernhard Kainz +3
Anatomical atlases are widely used for population studies and analysis. Conditional atlases target a specific sub-population defined via certain conditions, such as demographics or…
Body Fat Estimation from Surface Meshes using Graph Neural Networks
Tamara T. Mueller, Siyu Zhou, Sophie Starck +7
Body fat volume and distribution can be a strong indication for a person's overall health and the risk for developing diseases like type 2 diabetes and cardiovascular diseases. Fre…
Interpretable 2D Vision Models for 3D Medical Images
Alexander Ziller, Ayhan Can Erdur, Marwa Trigui +9
Training Artificial Intelligence (AI) models on 3D images presents unique challenges compared to the 2D case: Firstly, the demand for computational resources is significantly highe…
Private, fair and accurate: Training large-scale, privacy-preserving AI models in medical imaging
Soroosh Tayebi Arasteh, Alexander Ziller, Christiane Kuhl +6
Artificial intelligence (AI) models are increasingly used in the medical domain. However, as medical data is highly sensitive, special precautions to ensure its protection are requ…