X Ray Projection

X-ray projection imaging, fundamental to medical imaging and other applications, is undergoing significant advancements driven by the need for faster, more efficient, and less radiation-intensive techniques. Current research focuses on developing novel algorithms, including transformer networks and Gaussian splatting, to reconstruct high-quality 3D images from limited or sparse X-ray projections, often leveraging deep learning for feature extraction and image reconstruction. These improvements aim to enhance diagnostic capabilities, particularly in applications like computed tomography (CT) and image-guided radiation therapy, by reducing scan times and radiation exposure while maintaining or improving image quality.