Advertisement

Retrospective Blind MR Image Recovery with Parametrized Motion Models

  • Tim J. ParbsEmail author
  • Anita Mӧller
  • Alfred Mertins
Conference paper
Part of the Informatik aktuell book series (INFORMAT)

Zusammenfassung

In this paper, we present an alternating retrospective MRI reconstruction framework based on a parametrized motion model. An image recovery algorithm promoting sparsity is used in tandem with a numeric parameter search to iteratively reconstruct a sharp image. Additionally, we introduce a multiresolution strategy to restrict the numeric complexity. This algorithm is then tested in conjunction with a simple motion model on simulated data and provides robust and fast reconstruction of sharp images from severely corrupted k-spaces.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Literatur

  1. 1.
    Loktyushin A, Nickisch H, Pohmann R, et al. Blind retrospective motion correction of MR images. Magn Reson Med. 2013;70(6):1608–1618.CrossRefGoogle Scholar
  2. 2.
    Parikh N, Boyd S. Proximal algorithms. Found Trends Optim. 2014;1(3):127–239.MathSciNetCrossRefGoogle Scholar
  3. 3.
    Forney GD. The viterbi algorithm. Proc IEEE. 1973;61:268 – 278.MathSciNetCrossRefGoogle Scholar
  4. 4.
    Pipe JG. Motion correction with PROPELLER MRI: application to head motion and free-breathing cardiac imaging. Magn Reson Med. 1999;42(5):963–969.CrossRefGoogle Scholar
  5. 5.
    Cocosco CA, Kollokian V, Kwan RKS, et al. BrainWeb: online interface to a 3D MRI simulated brain database. NeuroImage. 1997;5:425.Google Scholar

Copyright information

© Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2019

Authors and Affiliations

  1. 1.Institut für SignalverarbeitungUniversität zu LübeckLübeckDeutschland

Personalised recommendations