Image-based EPI ghost correction using an algorithm based on projection onto convex sets (POCS)

This work describes the use of a method, based on the projection onto convex sets (POCS) algorithm, for reduction of the N/2 ghost in echo-planar imaging (EPI). In this method, ghosts outside the parent image are set to zero and a model k-space is obtained from the Fourier transform (FT) of the resulting image. The zeroth- and first-order phase corrections for each line of the original k-space are estimated by comparison with the corresponding line in the model k-space. To overcome problems of phase wrapping, the first-order phase corrections for the lines of the original k-space are estimated by registration with the corresponding lines in the model k-space. It is shown that applying these corrections will result in a reduction of the ghost, and that iterating the process will result in a convergence towards an image in which the ghost is minimized. The method is tested on spin-echo EPI data. The results show that the method is robust and remarkably effective, reducing the N/2 ghost to a level nearly comparable to that achieved with reference scans.