Accelerating non-contrast-enhanced MR angiography with inflow inversion recovery imaging by skipped phase encoding and edge deghosting (SPEED)

Improving image quality for skipped phase encoding and edge deghosting (SPEED) by exploiting several sparsifying transforms

PURPOSE

To improve the image quality of skipped phase encoding and edge deghosting (SPEED) by exploiting several sparsifying transforms.

METHODS

The SPEED technique uses a skipped phase encoding (PE) step to accelerate MRI scan. Previously, a difference transform (DT) along PE direction is used to obtain sparse ghosted-edge maps, which were modeled by a double layer ghost model and was then deghosted by a least square error solution. In this work, it is hypothesized that enhanced sparsity, and thus improved image quality may be achievable with other sparsifying transforms, including discrete wavelet transform (DWT), discrete cosine transform (DCT), DWT combined with DT, and DCT combined with DT.

RESULTS

For images of human subjects, SPEED with DWT or DCT can yield higher image quality than DT only, especially for those images with low contrast. Reconstruction error can be further reduced if DWT or DCT are combined with DT.

CONCLUSION

Image sparsity can be enhanced with more advanced transforms, leading to higher reconstruction quality in SPEED imaging that is desirable for practical MRI applications.

Suppressing multi-channel ultra-low-field MRI measurement noise using data consistency and image sparsity

Ultra-low-field (ULF) MRI (B₀ = 10–100 µT) typically suffers from a low signal-to-noise ratio (SNR). While SNR can be improved by pre-polarization and signal detection using highly sensitive superconducting quantum interference device (SQUID) sensors, we propose to use the inter-dependency of the k-space data from highly parallel detection with up to tens of sensors readily available in the ULF MRI in order to suppress the noise. Furthermore, the prior information that an image can be sparsely represented can be integrated with this data consistency constraint to further improve the SNR. Simulations and experimental data using 47 SQUID sensors demonstrate the effectiveness of this data consistency constraint and sparsity prior in ULF-MRI reconstruction.

Accelerated MRI by SPEED with generalized sampling schemes

PURPOSE

To enhance the fast imaging technique of skipped phase encoding (PE) and edge deghosting (SPEED) for more general sampling options, and thus more flexibility in implementations and applications.

METHODS

SPEED uses skipped PE steps to accelerate MRI scan. Previously, the PE skip size was chosen from prime numbers only. This restriction has been relaxed in this study to allow choice of any integers rather than merely prime numbers. Various sampling patterns were studied under all possible combinations of PE skip size and PE shifts. A criterion based on the rank values of ghost phasor matrices was introduced to evaluate SPEED reconstruction.

RESULTS

The reconstruction quality was found to correlate with the rank value of the ghost phasor matrix and the skipped PE size N. A low-rank value indicates a singular matrix that causes failure of the SPEED reconstruction. Composite numbers combined with appropriately chosen PE shifts yielded satisfactory reconstruction results.

CONCLUSION

With properly chosen PE shifts, it was found that any integers, including both prime numbers and composite numbers, could be used as PE skip size for SPEED. This finding allows much more flexible data acquisition options that may lead to more freedom in practical implementations and applications.