Paper ID: 2403.00771

XProspeCT: CT Volume Generation from Paired X-Rays

Benjamin Paulson, Joshua Goldshteyn, Sydney Balboni, John Cisler, Andrew Crisler, Natalia Bukowski, Julia Kalish, Theodore Colwell

Computed tomography (CT) is a beneficial imaging tool for diagnostic purposes. CT scans provide detailed information concerning the internal anatomic structures of a patient, but present higher radiation dose and costs compared to X-ray imaging. In this paper, we build on previous research to convert orthogonal X-ray images into simulated CT volumes by exploring larger datasets and various model structures. Significant model variations include UNet architectures, custom connections, activation functions, loss functions, optimizers, and a novel back projection approach.

Submitted: Feb 11, 2024