Photon Counting Computed Tomography

Photon-counting computed tomography (PCCT) leverages detectors that count individual X-ray photons, offering superior energy and spatial resolution compared to traditional CT. Current research heavily emphasizes improving PCCT image quality through deep learning techniques, particularly using denoising diffusion probabilistic models and unrolled iterative networks for image reconstruction and super-resolution, often incorporating model-based iterative refinement to address data limitations. These advancements aim to reduce radiation dose, increase imaging speed, and enhance diagnostic accuracy, particularly for applications like material decomposition and improved tissue characterization in various clinical settings.