36 citations · 88 across the 21 of their papers we have counts for
4 papers · 1 filter
Multi-Material Decomposition Using Spectral Diffusion Posterior Sampling
Xiao Jiang, Grace J. Gang, J. Webster Stayman
Many spectral CT applications require accurate material decomposition. Existing material decomposition algorithms are often susceptible to significant noise magnification or, in th…
Deep Learning CT Image Restoration using System Blur and Noise Models
Yijie Yuan, Grace J. Gang, J. Webster Stayman
The restoration of images affected by blur and noise has been widely studied and has broad potential for applications including in medical imaging modalities like computed tomograp…
Strategies for CT Reconstruction using Diffusion Posterior Sampling with a Nonlinear Model
Xiao Jiang, Shudong Li, Peiqing Teng +2
Diffusion Posterior Sampling(DPS) methodology is a novel framework that permits nonlinear CT reconstruction by integrating a diffusion prior and an analytic physical system model,…
CT Material Decomposition using Spectral Diffusion Posterior Sampling
Xiao Jiang, Grace J. Gang, J. Webster Stayman
In this work, we introduce a new deep learning approach based on diffusion posterior sampling (DPS) to perform material decomposition from spectral CT measurements. This approach c…