Joint reconstruction and scatter estimation in cone-beam CT using diffusion posterior sampling
Year: 2025
Type: conference-paper
Abstract: X-ray scatter degrades image quality in computed tomography, particularly in cone-beam CT due to wide cone angles. While mono-energetic CT scatter correction is well-studied, spectral CT imaging presents additional challenges due to its sensitivity to unmodeled biases in material decomposition and density estimation. This work presents a joint estimation approach that simultaneously estimates scatter and material densities by integrating the scatter component into a spectral CT forward model. Using Diffusion Posterior Sampling method, we leverage the combination of prior knowledge from large dataset training and the physical model for joint density and scatter estimation. Tested on simulated and phantom data, our method significantly reduce artifacts associated with unestimated scatter, improving spectral CT image quality.
DOI: 10.1117/12.3047684
Authors: Altea Lorenzon, Xiao Jiang, Grace J. Gang, J. Webster Stayman
Institutions: Johns Hopkins University, University of Pennsylvania
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Award: G2141967504
OpenAlex ID: W4409252965
