6 citations · 13 across the 23 of their papers we have counts for
5 papers · 1 filter
SciFusion: Physics-Guided Compositional Diffusion for Multimodal 3D Scientific Image Generation
Luoxi Wang, Alessio Quercia, Hanno Scharr +1
Existing 3D generative approaches are typically developed for individual imaging modalities, requiring substantial modality-specific data and limiting their ability to exploit shar…
Physics-Guided Diffusion Priors for Multi-Slice Reconstruction in Scientific Imaging
Laurentius Valdy, Richard D. Paul, Alessio Quercia +4
Accurate multi-slice reconstruction from limited measurement data is crucial to speed up the acquisition process in medical and scientific imaging. However, it remains challenging…
Efficient Epistemic Uncertainty Estimation in Cerebrovascular Segmentation
Omini Rathore, Richard Paul, Abigail Morrison +2
Brain vessel segmentation of MR scans is a critical step in the diagnosis of cerebrovascular diseases. Due to the fine vessel structure, manual vessel segmentation is time consumin…
MRI Reconstruction with Regularized 3D Diffusion Model (R3DM)
Arya Bangun, Zhuo Cao, Alessio Quercia +2
Magnetic Resonance Imaging (MRI) is a powerful imaging technique widely used for visualizing structures within the human body and in other fields such as plant sciences. However, t…
Untrained Perceptual Loss for image denoising of line-like structures in MR images
Elisabeth Pfaehler, Daniel Pflugfelder, Hanno Scharr
In the acquisition of Magnetic Resonance (MR) images shorter scan times lead to higher image noise. Therefore, automatic image denoising using deep learning methods is of high inte…