title: Reconstruction of undersampled radial PatLoc imaging using total generalized variation.
abstract: In the case of radial imaging with nonlinear spatial encoding fields, a prominent star-shaped artifact has been observed if a spin distribution is encoded with an undersampled trajectory. This work presents a new iterative reconstruction method based on the total generalized variation, which reduces this artifact. For this approach, a sampling operator (as well as its adjoint) is needed that maps data from PatLoc k-space to the final image space. It is shown that this can be realized as a type-3 nonuniform fast Fourier transform, which is implemented by a combination of a type-1 and type-2 nonuniform fast Fourier transform. Using this operator, it is also possible to implement an iterative conjugate gradient SENSE based method for PatLoc reconstruction, which leads to a significant reduction of computation time in comparison to conventional PatLoc image reconstruction methods. Results from numerical simulations and in vivo PatLoc measurements with as few as 16 radial projections are presented, which demonstrate significant improvements in image quality with the total generalized variation-based approach.
authors: Institute of Medical Engineering, Graz University of Technology, Kronesgasse 5, A-8010 Graz, Austria. florian.knoll@tugraz.at
authors: Florian
authors: F
authors: Knoll
authors: Gerrit
authors: G
authors: Schultz
authors: Kristian
authors: K
authors: Bredies
authors: Daniel
authors: D
authors: Gallichan
authors: Maxim
authors: M
authors: Zaitsev
authors: Jürgen
authors: J
authors: Hennig
authors: Rudolf
authors: R
authors: Stollberger
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D018401:Sample Size; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted