13 citations · 47 across the 12 of their papers we have counts for
4 papers · 1 filter
CT Reconstruction using Diffusion Posterior Sampling conditioned on a Nonlinear Measurement Model
Shudong Li, Xiao Jiang, Matthew Tivnan +3
Diffusion models have been demonstrated as powerful deep learning tools for image generation in CT reconstruction and restoration. Recently, diffusion posterior sampling, where a s…
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…
How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk Control
Jacopo Teneggi, Matthew Tivnan, J. Webster Stayman +1
Score-based generative modeling, informally referred to as diffusion models, continue to grow in popularity across several important domains and tasks. While they provide high-qual…