English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Self‐calibrated trajectory estimation and signal correction method for robust radial imaging using GRAPPA operator gridding

MPS-Authors
There are no MPG-Authors in the publication available
External Resource
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Deshmane, A., Blaimer, M., Breuer, F., Jakob, D., Duerk, J., Seiberlich, N., et al. (2016). Self‐calibrated trajectory estimation and signal correction method for robust radial imaging using GRAPPA operator gridding. Magnetic Resonance in Medicine, 75(2), 883-896. doi:10.1002/mrm.25648.


Cite as: https://hdl.handle.net/21.11116/0000-0006-9AD1-0
Abstract

Purpose

In radial imaging, projections may become “miscentered” due to gradient errors such as delays and eddy currents. These errors may result in image artifacts and can disrupt the reliability of direct current (DC) navigation. The proposed parallel imaging–based technique retrospectively estimates trajectory error from miscentered radial data without extra acquisitions, hardware, or sequence modification.
Theory and Methods

After phase correction, self‐calibrated GRAPPA operator gridding (GROG) weights are iteratively applied to shift‐miscentered projections toward the center of k‐space. A search algorithm identifies the shift that aligns the peak k‐space signals by maximizing the sum‐of‐squares DC signal estimate of each projection. The algorithm returns a trajectory estimate and a corrected radial k‐space signal.
Results

Data from a spherical phantom, the head, and the heart demonstrate that image reconstruction with the estimated trajectory restores image quality and reduces artifacts such as streaks and signal voids. The DC signal level is increased and variability is reduced.
Conclusion

Retrospective phase correction and iterative application of GROG can be used to successfully estimate the trajectory error in two‐dimensional radial acquisitions for improved image reconstruction without requiring extra data acquisition or sequence modification.