16 citations · 53 across the 7 of their papers we have counts for
3 papers · 1 filter
Gradient-Based Geometry Learning for Fan-Beam CT Reconstruction
Mareike Thies, Fabian Wagner, Noah Maul +10
Incorporating computed tomography (CT) reconstruction operators into differentiable pipelines has proven beneficial in many applications. Such approaches usually focus on the proje…
Generation of Anonymous Chest Radiographs Using Latent Diffusion Models for Training Thoracic Abnormality Classification Systems
Kai Packhäuser, Lukas Folle, Florian Thamm +1
The availability of large-scale chest X-ray datasets is a requirement for developing well-performing deep learning-based algorithms in thoracic abnormality detection and classifica…
Learned Cone-Beam CT Reconstruction Using Neural Ordinary Differential Equations
Mareike Thies, Fabian Wagner, Mingxuan Gu +3
Learned iterative reconstruction algorithms for inverse problems offer the flexibility to combine analytical knowledge about the problem with modules learned from data. This way, t…