Anh Tu Van1, Diego Hernando1, Joseph Holtrop2, Bradley P. Sutton2,3
1Electrical & Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States; 2Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States; 3Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, United States.
A robust 3D motion-induced phase error estimation and correction algorithm is introduced in the present study to enable in vivo 3D diffusion-weighted imaging. Parameters of the phase error are estimated by nonlinear fitting of navigator images to a motion-induced phase error model and used to correct the k-space data. The phase error parameter estimation is unbiased with mean square errors approaching the Cramer-Rao lower bound. The correction is time efficient with performance independent of the 3D k-space trajectory used. Simulation and in vivo results were obtained to demonstrate the accuracy of the proposed method.