Real-time MRI at a resolution of 20 ms

Martin Uecker, Shuo Zhang, Dirk Voit, Alexander Karaus, Klaus-Dietmar Merboldt, Jens Frahm

Research output: Contribution to journalArticlepeer-review


The desire to visualize noninvasively physiological processes at high temporal resolution has been a driving force for the development of MRI since its inception in 1973. In this article, we describe a unique method for real-time MRI that reduces image acquisition times to only 20 ms. Although approaching the ultimate limit of MRI technology, the method yields high image quality in terms of spatial resolution, signal-to-noise ratio and the absence of artifacts. As proposed previously, a fast low-angle shot (FLASH) gradient-echo MRI technique (which allows for rapid and continuous image acquisitions) is combined with a radial encoding scheme (which offers motion robustness and moderate tolerance to data undersampling) and, most importantly, an iterative image reconstruction by regularized nonlinear inversion (which exploits the advantages of parallel imaging with multiple receiver coils). In this article, the extension of regularization and filtering to the temporal domain exploits consistencies in successive data acquisitions and thereby enhances the degree of radial undersampling in a hitherto unexpected manner by one order of magnitude. The results obtained for turbulent flow, human speech production and human heart function demonstrate considerable potential for real-time MRI studies of dynamic processes in a wide range of scientific and clinical settings.

Original languageEnglish
Pages (from-to)986-94
Number of pages9
JournalNMR in Biomedicine
Issue number8
Publication statusPublished - Oct 2010
Externally publishedYes


  • Heart/anatomy & histology
  • Humans
  • Hydrodynamics
  • Image Interpretation, Computer-Assisted/methods
  • Image Processing, Computer-Assisted/methods
  • Magnetic Resonance Imaging/methods
  • Signal Processing, Computer-Assisted
  • Speech/physiology
  • Time Factors

Fields of Expertise

  • Human- & Biotechnology
  • Information, Communication & Computing


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