Wavelet-space correlation imaging for high-speed MRI without motion monitoring or data segmentation

Magn Reson Med. 2015 Dec;74(6):1574-86. doi: 10.1002/mrm.25546. Epub 2014 Dec 2.

Abstract

Purpose: This study aims to (i) develop a new high-speed MRI approach by implementing correlation imaging in wavelet-space, and (ii) demonstrate the ability of wavelet-space correlation imaging to image human anatomy with involuntary or physiological motion.

Methods: Correlation imaging is a high-speed MRI framework in which image reconstruction relies on quantification of data correlation. The presented work integrates correlation imaging with a wavelet transform technique developed originally in the field of signal and image processing. This provides a new high-speed MRI approach to motion-free data collection without motion monitoring or data segmentation. The new approach, called "wavelet-space correlation imaging", is investigated in brain imaging with involuntary motion and chest imaging with free-breathing.

Results: Wavelet-space correlation imaging can exceed the speed limit of conventional parallel imaging methods. Using this approach with high acceleration factors (6 for brain MRI, 16 for cardiac MRI, and 8 for lung MRI), motion-free images can be generated in static brain MRI with involuntary motion and nonsegmented dynamic cardiac/lung MRI with free-breathing.

Conclusion: Wavelet-space correlation imaging enables high-speed MRI in the presence of involuntary motion or physiological dynamics without motion monitoring or data segmentation.

Keywords: correlation imaging; data correlation function; high-speed MRI.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Artifacts*
  • Brain / anatomy & histology
  • Heart / anatomy & histology
  • Humans
  • Image Enhancement / methods*
  • Image Interpretation, Computer-Assisted / methods*
  • Lung / anatomy & histology
  • Magnetic Resonance Imaging / methods*
  • Motion
  • Reproducibility of Results
  • Sample Size
  • Sensitivity and Specificity
  • Signal Processing, Computer-Assisted*
  • Statistics as Topic
  • Wavelet Analysis*