36 citations · 55 across the 5 of their papers we have counts for
5 papers
Stationary CT Imaging of Intracranial Hemorrhage with Diffusion Posterior Sampling Reconstruction
Alejandro Lopez-Montes, Thomas McSkimming, Anthony Skeats +4
Diffusion Posterior Sampling (DPS) can be used in Computed Tomography (CT) reconstruction by leveraging diffusion-based generative models for unconditional image synthesis while ma…
Using Uncertainty in Deep Learning Reconstruction for Cone-Beam CT of the Brain
Pengwei Wu, Alejandro Sisniega, Ali Uneri +7
Contrast resolution beyond the limits of conventional cone-beam CT (CBCT) systems is essential to high-quality imaging of the brain. We present a deep learning reconstruction metho…
C-Arm Non-Circular Orbits: Geometric Calibration, Image Quality, and Avoidance of Metal Artifacts
Pengwei Wu, Niral Sheth, Alejandro Sisniega +12
Metal artifacts present a frequent challenge to cone-beam CT (CBCT) in image-guided surgery, obscuring visualization of metal instruments and adjacent anatomy. Recent advances in m…
High-Fidelity Modeling of Detector Lag and Gantry Motion in CT Reconstruction
Steven Tilley, Alejandro Sisniega, Jeffrey H. Siewerdsen +1
Detector lag and gantry motion during x-ray exposure and integration both result in azimuthal blurring in CT reconstructions. These effects can degrade image quality both for high-…
Penalized-Likelihood Reconstruction with High-Fidelity Measurement Models for High-Resolution Cone-Beam Imaging
Steven Tilley, Matthew Jacobson, Qian Cao +4
We present a novel reconstruction algorithm based on a general cone-beam CT forward model which is capable of incorporating the blur and noise correlations that are exhibited in fl…