2 Dimensional X Ray

Two-dimensional X-ray imaging, while offering low radiation exposure, lacks the detailed three-dimensional information provided by computed tomography (CT). Current research focuses on reconstructing 3D CT images from 2D X-ray projections using deep learning models, particularly diffusion models, generative adversarial networks (GANs), and transformer networks, often incorporating techniques like edge-aware processing and attenuation correction to improve accuracy. These advancements aim to provide high-resolution 3D imaging with reduced radiation exposure, impacting medical diagnostics, surgical planning, and potentially other fields like materials science where high-throughput analysis of 2D X-ray scattering data is needed. The ultimate goal is to bridge the gap between the speed and low radiation of 2D X-rays and the detailed information of CT scans.