8 papers
CTorch: PyTorch-Compatible GPU-Accelerated Auto-Differentiable Projector Toolbox for Computed Tomography
Xiao Jiang, Grace J. Gang, J. Webster Stayman
This work introduces CTorch, a PyTorch-compatible, GPU-accelerated, and auto-differentiable projector toolbox designed to handle various CT geometries with configurable projector a…
Differentiable Forward and Back-Projector for Rigid Motion Estimation in X-ray Imaging
Xiao Jiang, Xin Wang, Ali Uneri +2
Objective: In this work, we propose a framework for differentiable forward and back-projector that enables scalable, accurate, and memory-efficient gradient computation for rigid m…
Volumetric Material Decomposition Using Spectral Diffusion Posterior Sampling with a Compressed Polychromatic Forward Model
Xiao Jiang, Grace J. Gang, J. Webster Stayman
We have previously introduced Spectral Diffusion Posterior Sampling (Spectral DPS) as a framework for accurate one-step material decomposition by integrating analytic spectral syst…
Conformal Risk Control for Semantic Uncertainty Quantification in Computed Tomography
Jacopo Teneggi, J Webster Stayman, Jeremias Sulam
Uncertainty quantification is necessary for developers, physicians, and regulatory agencies to build trust in machine learning predictors and improve patient care. Beyond measuring…
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…