XProspeCT: CT Volume Generation from Paired X-Rays
This addresses a problem for medical imaging by potentially improving diagnostic tools, but it appears incremental as it builds on previous research.
The paper tackled generating CT volumes from paired X-ray images to reduce radiation dose and costs, achieving results through exploration of larger datasets and various model structures, though no concrete numbers are provided.
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.