4 citations · 8 across the 5 of their papers we have counts for
5 papers
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…
A Joint Processing Strategy for Image Quality Improvement in 3D Digital Subtraction Angiography
Xiaoxuan Zhang, Xiao Jiang, Matthew Tivnan +2
Three-dimensional digital subtraction angiography (3D-DSA) is a widely adopted technique for clinical evaluation of contrast-enhanced vasculatures. The distribution of a contrast a…
Fourier Diffusion Models: A Method to Control MTF and NPS in Score-Based Stochastic Image Generation
Matthew Tivnan, Jacopo Teneggi, Tzu-Cheng Lee +6
Score-based stochastic denoising models have recently been demonstrated as powerful machine learning tools for conditional and unconditional image generation. The existing methods…