Computed Tomography Trajectory

Computed tomography (CT) trajectory optimization aims to improve the efficiency and quality of CT scans by intelligently selecting the path of the X-ray source around the object. Current research focuses on developing algorithms, such as gated recurrent units (GRUs) and integer programming methods, to design optimal trajectories that maximize image quality metrics like contrast and resolution while minimizing scan time and data redundancy. These advancements address limitations of traditional circular and helical scans, particularly for large or complex objects and systems with multiple robotic arms, leading to more efficient and cost-effective CT imaging across various applications.