Document Type
Article
Language
eng
Publication Date
4-2016
Publisher
Elsevier
Source Publication
Magnetic Resonance Imaging
Source ISSN
0730-725X
Original Item ID
DOI: 10.1016/j.mri.2015.11.003
Abstract
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.
Recommended Citation
Rowe, Daniel B.; Bruce, Iain P.; Nencka, Andrew S.; Hyde, James S.; and Kociuba, Mary C., "Separation of Parallel Encoded Complex-Valued Slices (SPECS) From A Single Complex-Valued Aliased Coil Image" (2016). Mathematics, Statistics and Computer Science Faculty Research and Publications. 426.
https://epublications.marquette.edu/mscs_fac/426
Comments
Accepted version. Magnetic Resonance Imaging, Vol. 34, No. 3 (April 2016): 359-369. DOI. © 2016 Elsevier. Used with permission.
NOTICE: this is the author’s version of a work that was accepted for publication in Magnetic Resonance Imaging. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Magnetic Resonance Imaging, VOL. 34, ISSUE 3, April 2016, DOI.