Cartesian K Space Trajectory

Cartesian k-space trajectories are a central element in various fields, from magnetic resonance imaging (MRI) reconstruction to robot trajectory generation and pedestrian behavior analysis. Current research focuses on efficiently representing and manipulating high-dimensional trajectory data, often employing manifold learning, flow-based models, and transformer networks to capture complex relationships and generate realistic trajectories from limited data or textual descriptions. These advancements improve the accuracy and efficiency of tasks like MRI reconstruction, robot control (including safety-critical applications), and prediction of human movement, ultimately leading to more robust and reliable systems in diverse applications.