20 citations · 20 across the 6 of their papers we have counts for
6 papers
Differentiable Score-Based Likelihoods: Learning CT Motion Compensation From Clean Images
Mareike Thies, Noah Maul, Siyuan Mei +8
Motion artifacts can compromise the diagnostic value of computed tomography (CT) images. Motion correction approaches require a per-scan estimation of patient-specific motion patte…
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…
The fate of Galilean relativity in minimal-length theories
Pasquale Bosso, Giuseppe Fabiano, Domenico Frattulillo +1
A number of arguments at the interplay of general relativity and quantum theory suggest an operational limit to spatial resolution, conventionally modelled as a generalized uncerta…
Handling Label Uncertainty on the Example of Automatic Detection of Shepherd's Crook RCA in Coronary CT Angiography
Felix Denzinger, Michael Wels, Oliver Taubmann +10
Coronary artery disease (CAD) is often treated minimally invasively with a catheter being inserted into the diseased coronary vessel. If a patient exhibits a Shepherd's Crook (SC)…
Trainable Joint Bilateral Filters for Enhanced Prediction Stability in Low-dose CT
Fabian Wagner, Mareike Thies, Felix Denzinger +7
Low-dose computed tomography (CT) denoising algorithms aim to enable reduced patient dose in routine CT acquisitions while maintaining high image quality. Recently, deep learning~(…
Curved momentum space equivalent to the linear and quadratic Generalized Uncertainty Principle
Fabian Wagner
In this work, we deepen the correspondence between Generalized Uncertainty Principles (GUPs) and quantum dynamics on curved momentum space. In particular, we investigate the linear…