A Resampling of Calibration Images for a Multi-Coil Separation of Parallel Encoded Complex-valued Slices in fMRI

Increasing temporal resolution while mitigating signal leakage has been a challenge of simultaneous multi-slice (SMS) imaging in functional magnetic resonance imaging. The MultiCoil Separation of Parallel Encoded Complex-valued Slices (mSPECS) reconstruction method minimizes residual signal artifacts from time-series un-aliasing, and preserves the blood oxygen level dependent (BOLD) signal in fMRI studies. In the mSPECS reconstruction model, multiple slices are simultaneously excited with a Hadamard multiband pulse sequence. With Hadamard encoded acquisitions, the separated images have increased sensitivity with no net reduction in the scan duration. The mSPECS reconstruction method has incorporated the spatial information from a phased array of receiver coils, combined with a bootstrap sampling and artificial Hadamard aliasing of calibration images, to separate the fMRI time-series with a visual task in a least squares estimation. Faster brain function observation is dynamically achieved post data acquisition in a visual task fMRI experiment. The aliased slices are effectively separated, and functional activation is detected in the visual cortex. The mSPECS model has combined calibration images with intrinsic orthogonal properties of Hadamard encoding, into a un-aliasing estimator to achieve separated images of fMRI time-series.