title: Data extrapolation for truncation artifact removal.
abstract: Clinicians typically obtain high-resolution clinical MR images in an effort to avoid the truncation artifacts that often arise in Fourier transform reconstruction of limited data. A method for reducing these artifacts in MR images, at the reconstruction stage, would allow for reduced imaging times, through the collection of fewer phase encode steps and increased signal-to-noise ratios, through increased pixel size. The approach to reducing truncation artifacts in MR images is developed and a simple algorithm is presented which significantly reduces truncation artifacts in images with as few as 96 phase encode steps. The algorithm is compared with a more sophisticated method of reconstructing truncation-free images and is shown to be equivalently effective. Three clinical examples are shown illustrating the success of the method.
authors.affiliation: Department of Medical Biophysics, University of Toronto, Canada.
authors.forename: R T
authors.initials: RT
authors.lastname: Constable
authors.forename: R M
authors.initials: RM
authors.lastname: Henkelman
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology; D005583:Fourier Analysis; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007719:Knee Joint / Q000033:anatomy & histology; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000706:statistics & numerical data; D008962:Models, Theoretical