30 citations · 96 across the 28 of their papers we have counts for
6 papers · 1 filter
Focus on Content not Noise: Improving Image Generation for Nuclei Segmentation by Suppressing Steganography in CycleGAN
Jonas Utz, Tobias Weise, Maja Schlereth +5
Annotating nuclei in microscopy images for the training of neural networks is a laborious task that requires expert knowledge and suffers from inter- and intra-rater variability, e…
Task-based Generation of Optimized Projection Sets using Differentiable Ranking
Linda-Sophie Schneider, Mareike Thies, Christopher Syben +3
We present a method for selecting valuable projections in computed tomography (CT) scans to enhance image reconstruction and diagnosis. The approach integrates two important factor…
Exploring Epipolar Consistency Conditions for Rigid Motion Compensation in In-vivo X-ray Microscopy
Mareike Thies, Fabian Wagner, Mingxuan Gu +10
Intravital X-ray microscopy (XRM) in preclinical mouse models is of vital importance for the identification of microscopic structural pathological changes in the bone which are cha…
Transient Hemodynamics Prediction Using an Efficient Octree-Based Deep Learning Model
Noah Maul, Katharina Zinn, Fabian Wagner +6
Patient-specific hemodynamics assessment could support diagnosis and treatment of neurovascular diseases. Currently, conventional medical imaging modalities are not able to accurat…
Optimizing CT Scan Geometries With and Without Gradients
Mareike Thies, Fabian Wagner, Noah Maul +4
In computed tomography (CT), the projection geometry used for data acquisition needs to be known precisely to obtain a clear reconstructed image. Rigid patient motion is a cause fo…
Geometric Constraints Enable Self-Supervised Sinogram Inpainting in Sparse-View Tomography
Fabian Wagner, Mareike Thies, Noah Maul +5
The diagnostic quality of computed tomography (CT) scans is usually restricted by the induced patient dose, scan speed, and image quality. Sparse-angle tomographic scans reduce rad…