Zobrazeno 1 - 10
of 555
pro vyhledávání: '"Wagner, Fabian"'
Autor:
Thies, Mareike, Wagner, Fabian, Maul, Noah, Mei, Siyuan, Gu, Mingxuan, Pfaff, Laura, Vysotskaya, Nastassia, Yu, Haijun, Maier, Andreas
Computed tomography (CT) relies on precise patient immobilization during image acquisition. Nevertheless, motion artifacts in the reconstructed images can persist. Motion compensation methods aim to correct such artifacts post-acquisition, often inco
Externí odkaz:
http://arxiv.org/abs/2405.19079
We study the weak equivalence principle in the context of modified dispersion relations, a prevalent approach to quantum gravity phenomenology. We find that generic modified dispersion relations violate the weak equivalence principle. The acceleratio
Externí odkaz:
http://arxiv.org/abs/2404.18811
Autor:
Mei, Siyuan, Fan, Fuxin, Thies, Mareike, Gu, Mingxuan, Wagner, Fabian, Aust, Oliver, Erceg, Ina, Mirzaei, Zeynab, Neag, Georgiana, Sun, Yipeng, Huang, Yixing, Maier, Andreas
Recently, X-ray microscopy (XRM) and light-sheet fluorescence microscopy (LSFM) have emerged as two pivotal imaging tools in preclinical research on bone remodeling diseases, offering micrometer-level resolution. Integrating these complementary modal
Externí odkaz:
http://arxiv.org/abs/2404.14807
Autor:
Thies, Mareike, Maul, Noah, Mei, Siyuan, Pfaff, Laura, Vysotskaya, Nastassia, Gu, Mingxuan, Utz, Jonas, Possart, Dennis, Folle, Lukas, Wagner, Fabian, Maier, Andreas
Motion artifacts can compromise the diagnostic value of computed tomography (CT) images. Motion correction approaches require a per-scan estimation of patient-specific motion patterns. In this work, we train a score-based model to act as a probabilit
Externí odkaz:
http://arxiv.org/abs/2404.14747
Autor:
Mei, Siyuan, Fan, Fuxin, Wagner, Fabian, Thies, Mareike, Gu, Mingxuan, Sun, Yipeng, Maier, Andreas
Deep learning-based medical image processing algorithms require representative data during development. In particular, surgical data might be difficult to obtain, and high-quality public datasets are limited. To overcome this limitation and augment d
Externí odkaz:
http://arxiv.org/abs/2404.03541
Modified dispersion relations (MDRs) provide a phenomenological approach beyond the Standard Model, intended to capture tentative nonperturbative quantum gravity effects. Here, we show how to constrain a large class of MDRs by deriving the explicit c
Externí odkaz:
http://arxiv.org/abs/2403.19389
Physics-Informed Learning for Time-Resolved Angiographic Contrast Agent Concentration Reconstruction
Autor:
Maul, Noah, Birkhold, Annette, Wagner, Fabian, Thies, Mareike, Rohleder, Maximilian, Berg, Philipp, Kowarschik, Markus, Maier, Andreas
Three-dimensional Digital Subtraction Angiography (3D-DSA) is a well-established X-ray-based technique for visualizing vascular anatomy. Recently, four-dimensional DSA (4D-DSA) reconstruction algorithms have been developed to enable the visualization
Externí odkaz:
http://arxiv.org/abs/2403.01993
Autor:
Utz, Jonas, Weise, Tobias, Schlereth, Maja, Wagner, Fabian, Thies, Mareike, Gu, Mingxuan, Uderhardt, Stefan, Breininger, Katharina
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, especially in fluorescence microscopy. Generative networks such as Cycl
Externí odkaz:
http://arxiv.org/abs/2308.01769
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 uncertainty principle (GUP). Recently, it has been demonstrated that the dyna
Externí odkaz:
http://arxiv.org/abs/2307.12109
In this paper, we investigate the consequences of maximal length as well as minimal momentum scales on nonlocal correlations shared by two parties of a bipartite quantum system. To this aim, we rely on a general phenomenological scheme which is usual
Externí odkaz:
http://arxiv.org/abs/2306.13067