Reinforcement Learning

Improve the reliability of tractography methods by reinforcement learning by using an oracle that quantifies the anatomical validity of a white matter (WM) fiber. We generate randomly new trajectories of a possible fiber from a failling fiber and select the best trajectory based on the oracle’s validity score.