Separation of parallel encoded complex-valued slices (SPECS) from a single complex-valued aliased coil image.

Journal Article

Purpose

Achieving a reduction in scan time with minimal inter-slice signal leakage is one of the significant obstacles in parallel MR imaging. In fMRI, multiband-imaging techniques accelerate data acquisition by simultaneously magnetizing the spatial frequency spectrum of multiple slices. The SPECS model eliminates the consequential inter-slice signal leakage from the slice unaliasing, while maintaining an optimal reduction in scan time and activation statistics in fMRI studies.

Materials and methods

When the combined k-space array is inverse Fourier reconstructed, the resulting aliased image is separated into the un-aliased slices through a least squares estimator. Without the additional spatial information from a phased array of receiver coils, slice separation in SPECS is accomplished with acquired aliased images in shifted FOV aliasing pattern, and a bootstrapping approach of incorporating reference calibration images in an orthogonal Hadamard pattern.

Result

The aliased slices are effectively separated with minimal expense to the spatial and temporal resolution. Functional activation is observed in the motor cortex, as the number of aliased slices is increased, in a bilateral finger tapping fMRI experiment.

Conclusion

The SPECS model incorporates calibration reference images together with coefficients of orthogonal polynomials into an un-aliasing estimator to achieve separated images, with virtually no residual artifacts and functional activation detection in separated images.

Full Text

Duke Authors

Cited Authors

  • Rowe, DB; Bruce, IP; Nencka, AS; Hyde, JS; Kociuba, MC

Published Date

  • April 2016

Published In

Volume / Issue

  • 34 / 3

Start / End Page

  • 359 - 369

PubMed ID

  • 26612076

Pubmed Central ID

  • 26612076

Electronic International Standard Serial Number (EISSN)

  • 1873-5894

International Standard Serial Number (ISSN)

  • 0730-725X

Digital Object Identifier (DOI)

  • 10.1016/j.mri.2015.11.003

Language

  • eng