K-space Inherited Parallel Acquisition (KIPA): application on dynamic magnetic resonance imaging thermometry

Jun Yu Guo, Eugene G. Kholmovski, Ling Zhang, Eun Kee Jeong, Dennis L. Parker

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

In this study, a novel method for dynamic parallel image acquisition and reconstruction is presented. In this method, called k-space inherited parallel acquisition (KIPA), localized reconstruction coefficients are used to achieve higher reduction factors, and lower noise and artifact levels compared to that of generalized autocalibrating partially parallel acquisition (GRAPPA) reconstruction. In KIPA, the full k-space for the first frame and the partial k-space for later frames are required to reconstruct a whole series of images. Reconstruction coefficients calculated for different segments of k-space from the first frame data set are used to estimate missing k-space lines in corresponding k-space segments of other frames. The local determination of KIPA reconstruction coefficients is essential to adjusting them according to the local signal-to-noise ratio characteristics of k-space data. The proposed algorithm is applicable to dynamic imaging with arbitrary k-space sampling trajectories. Simulations of magnetic resonance thermometry using the KIPA method with a reduction factor of 6 and using dynamic imaging studies of human subjects with reduction factors of 4 and 6 have been performed to prove the feasibility of our method and to show apparent improvement in image quality in comparison with GRAPPA for dynamic imaging.

Original languageEnglish (US)
Pages (from-to)903-915
Number of pages13
JournalMagnetic Resonance Imaging
Volume24
Issue number7
DOIs
StatePublished - Sep 2006
Externally publishedYes

Keywords

  • Dynamic imaging
  • GRAPPA
  • MRI
  • MRI thermometry
  • Parallel imaging

ASJC Scopus subject areas

  • Biophysics
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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