4 citations · 7 across the 5 of their papers we have counts for
5 papers
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,…
Noise suppression in photon-counting CT using unsupervised Poisson flow generative models
Dennis Hein, Staffan Holmin, Timothy Szczykutowicz +4
Deep learning has proven to be important for CT image denoising. However, such models are usually trained under supervision, requiring paired data that may be difficult to obtain i…
Ring Artifact Correction in Photon-Counting Spectral CT Using a Convolutional Neural Network With Spectral Loss
Dennis Hein, Konstantinos Liappis, Fredrik Grönberg +2
Photon-counting spectral computed tomography is now clinically available. These new detectors come with the promise of higher contrast-to-noise ratio and spatial resolution and imp…
Dimensionality and Background Cancellation in Energy Selective X-Ray Imaging
Fredrik Grönberg, Mats Persson, Hans Bornefalk
Purpose: The set of linear attenuation coefficients that belong to materials in the human body is commonly assumed to be spanned by two basis functions in the range of clinical x-r…
Deep Learning for Material Decomposition in Photon-Counting CT
Alma Eguizabal, Ozan Öktem, Mats U. Persson
Photon-counting CT (PCCT) offers improved diagnostic performance through better spatial and energy resolution, but developing high-quality image reconstruction methods that can dea…