27 citations · 27 across the 6 of their papers we have counts for
6 papers
Dual-domain U-Nets with embedded back projection operators for motion-resolved 4D CBCT reconstruction
Ivo Herzig, Pascal Paysan, Daniel Barco +8
Four-dimensional cone beam CT (4D CBCT) is important for image-guided radiation therapy of thoracic cancers, but its use is limited by long scan times, causing high patient dose an…
Projected Energy Matching for Generative 3D Priors
Daniel Barco, Michal Balcerak, Suprosanna Shit +4
Transport-based generative models, which learn a time-dependent vector field that moves noise to data, have become a dominant paradigm. However, these models typically do not expli…
The Role of Artificial Intelligence in the SKA Era
Philipp Denzel, Frank-Peter Schilling, Elena Gavagnin
The Square Kilometre Array Observatory (SKAO) will usher in an era of unprecedented data complexity and scientific opportunity in radio astronomy, producing petabyte-scale datasets…
Optimization of Deep Learning Models for Radio Galaxy Classification
Philipp Denzel, Manuel Weiss, Elena Gavagnin +1
Modern radio telescope surveys, capable of detecting billions of galaxies in wide-field surveys, have made manual morphological classification impracticable. This applies in partic…
Galactic Alchemy: Deep Learning Map-to-Map Translation in Hydrodynamical Simulations
Philipp Denzel, Yann Billeter, Frank-Peter Schilling +1
We present the first systematic study of multi-domain map-to-map translation in galaxy formation simulations, leveraging deep generative models to predict diverse galactic properti…
Artifact Reduction in 3D and 4D Cone-beam Computed Tomography Images with Deep Learning -- A Review
Mohammadreza Amirian, Daniel Barco, Ivo Herzig +1
Deep learning based approaches have been used to improve image quality in cone-beam computed tomography (CBCT), a medical imaging technique often used in applications such as image…