Spectral CT

Spectral CT enhances traditional CT by capturing X-ray attenuation at multiple energy levels, enabling material decomposition and the creation of parametric maps revealing tissue composition (e.g., effective atomic number, electron density). Current research heavily utilizes deep learning, employing convolutional neural networks and diffusion-based models to improve image quality, speed up material decomposition, and even enable the generation of spectral information from single-energy scans. These advancements offer improved diagnostic capabilities, potentially leading to more accurate disease detection and treatment planning in various medical applications, as well as enhanced material characterization in non-medical fields.