Real-time Personalized Acquisition Optimization: 30%-50% reconstruction improvements from a 10-second undersampling optimization

Improved undersampling designs can effectively improve the acquisition and resulting reconstruction accuracy. However, existing undersampling optimization methods are time-consuming and the limited performance prevent their clinical applications. Here we proposed an improved undersampling trajectory optimization scheme to generate an optimized trajectory within seconds and apply for subsequent multi-contrast MRI datasets on a per-subject basis. By using a data-driven method combined with improved algorithm design, GPU acceleration and more efficient computation, the proposed method can optimize a trajectory within 5-10 seconds and achieve 30% - 50% reconstruction improvement with the same acquisition cost, which makes real-time under-sampling optimization possible for clinical applications.