Model-based simulation of dynamic magnetic resonance imaging signals

Jim Ji, Yuttapong Jiraraksopakun

Research output: Contribution to journalArticle

3 Citations (Scopus)


This paper presents a model-based method to efficiently simulate dynamic magnetic resonance imaging signals. Using an analytical spatiotemporal object model, the method can approximate time-varying k-space signals such as those from objects in motion and/or during dynamic contrast enhancement. Both rigid-body and non-rigid-body motions can be simulated using the proposed method. In addition, it can simulate data with arbitrary data sampling order and/or non-uniform k-space trajectory. A set of simulated images were compared with real data acquired from a rat model on a 4.7 T scanner to verify the model. The efficient simulation method is expected to be useful for rapid testing of various imaging and image analysis algorithms such as image reconstruction, image registration, motion compensation, and kinetic parameter mapping.

Original languageEnglish
Pages (from-to)305-311
Number of pages7
JournalBiomedical Signal Processing and Control
Issue number4
Publication statusPublished - Oct 2008
Externally publishedYes



  • Dynamic imaging
  • k-Space signal simulation
  • Magnetic resonance imaging
  • Motion artifacts
  • Non-Cartesian

ASJC Scopus subject areas

  • Health Informatics
  • Signal Processing

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