7 citations · 15 across the 5 of their papers we have counts for
5 papers
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…
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…
High-Sensitivity Iodine Imaging by Combining Spectral CT Technologies
Matthew Tivnan, Grace Gang, Wenchao Cao +3
Spectral CT offers enhanced material discrimination over single-energy systems and enables quantitative estimation of basis material density images. Water/iodine decomposition in c…
Combining Spectral CT Acquisition Methods for High-Sensitivity Material Decomposition
Matthew Tivnan, Wenying Wang, Grace Gang +3
Quantitative estimation of contrast agent concentration is made possible by spectral CT and material decomposition. There are several approaches to modulate the sensitivity of the…
Design of Spatial-Spectral Filters for CT Material Decomposition
Matthew Tivnan, Wenying Wang, Grace Gang +1
Spectral CT has shown promise for high-sensitivity quantitative imaging and material decomposition. This work presents a new device called a spatial-spectral filter (SSF) which con…