4 citations · 8 across the 7 of their papers we have counts for
3 papers · 1 filter
Physics-Inspired Generative Models in Medical Imaging: A Review
Dennis Hein, Afshin Bozorgpour, Dorit Merhof +1
Physics-inspired Generative Models (GMs), in particular Diffusion Models (DMs) and Poisson Flow Models (PFMs), enhance Bayesian methods and promise great utility in medical imaging…
PFCM: Poisson flow consistency models for low-dose CT image denoising
Dennis Hein, Grant Stevens, Adam Wang +1
X-ray computed tomography (CT) is widely used for medical diagnosis and treatment planning; however, concerns about ionizing radiation exposure drive efforts to optimize image qual…
PPFM: Image denoising in photon-counting CT using single-step posterior sampling Poisson flow generative models
Dennis Hein, Staffan Holmin, Timothy Szczykutowicz +4
Diffusion and Poisson flow models have shown impressive performance in a wide range of generative tasks, including low-dose CT image denoising. However, one limitation in general,…