title: Super-resolution for multislice diffusion tensor imaging.
abstract: Diffusion weighted magnetic resonance images are often acquired with single shot multislice imaging sequences, because of their short scanning times and robustness to motion. To minimize noise and acquisition time, images are generally acquired with either anisotropic or isotropic low resolution voxels, which impedes subsequent posterior image processing and visualization. In this article, we propose a super-resolution method for diffusion weighted imaging that combines anisotropic multislice images to enhance the spatial resolution of diffusion tensor data. Each diffusion weighted image is reconstructed from a set of arbitrarily oriented images with a low through-plane resolution. The quality of the reconstructed diffusion weighted images was evaluated by diffusion tensor metrics and tractography. Experiments with simulated data, a hardware DTI phantom, as well as in vivo human brain data were conducted. Our results show a significant increase in spatial resolution of the diffusion tensor data while preserving high signal to noise ratio.
authors.affiliation: Department of Medical informatics, BIGR, Erasmus Medical Center, Rotterdam, The Netherlands.
authors.forename: Dirk H J
authors.initials: DH
authors.lastname: Poot
authors.forename: Ben
authors.initials: B
authors.lastname: Jeurissen
authors.forename: Yannick
authors.initials: Y
authors.lastname: Bastiaensen
authors.forename: Jelle
authors.initials: J
authors.lastname: Veraart
authors.forename: Wim
authors.initials: W
authors.lastname: Van Hecke
authors.forename: Paul M
authors.initials: PM
authors.lastname: Parizel
authors.forename: Jan
authors.initials: J
authors.lastname: Sijbers
mesh_terms: D000328:Adult; D001921:Brain / Q000033:anatomy & histology; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement; D008297:Male; D019047:Phantoms, Imaging