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Abstract #5339

Novel Image-based Nyquist Ghost Correction of Diffusion-Weighted Echo Planar Imaging using Ghost/Object Minimization

Jessica A McKay1, Steen Moeller2, Sudhir Ramanna2, Edward J Auerbach2, Gregory J Metzger2, Justin R Ryder3, Kamil Ugurbil2, Essa Yacoub2, and Patrick J Bolan2

1Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States, 2Department of Radiology, University of Minnesota, Minneapolis, MN, United States, 3Department of Pediatrics, University of Minnesota, Minneapolis, MN, United States

Diffusion weighted imaging (DWI) acquired with SE-EPI is subject to Nyquist ghosts, which are commonly corrected using a three-line navigator. However, several alternative ghost correction strategies do not require any reference acquisition. These methods define a cost function that is minimized when the image is ghost-free. We propose a novel referenceless method called ghost/object minimization by defining the cost function as the summation over the image divided by its ½-FOV-shifted counterpart. In this work, we test noise sensitivity and demonstrate the feasibility of the ghost/object minimization using simulated ghosts and in vivo acquisitions including brain, prostate, breast, and liver DWI.

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