Wavelet Domain RF Pulse Design for MRI Simulations and Brain Imaging

This dataset supports a new method for designing radiofrequency (RF) pulses using numerical optimization in the wavelet domain for magnetic resonance imaging. It includes data from simulations and human brain imaging to demonstrate optimized slice profiles and reduced peak RF power for simultaneous multi-slice diffusion acquisitions. The dataset was authored by Andrew M. Huettner and last updated in June 2020.

Use Cases

• Analyze the relationship between wavelet domain coefficients and the resulting slice profile to understand compression properties in RF pulse design.
• Validate the algorithm's minimization of the L2-norm of the slice profile against simulated magnetization responses from a Bloch equation simulator.
• Compare peak RF power metrics between traditional and wavelet-optimized pulses for multiband simultaneous multi-slice (SMS) acquisitions.
• Investigate the trade-off between rejection band ripple penalization and net transverse magnetization maximization across slices in the optimization process.

Strengths

• Dataset is associated with a peer-reviewed scientific method for RF pulse design, published in 2020.
• Includes data from both numerical simulations and human brain imaging experiments.
• Released under the permissive CC0 1.0 public domain license.

Limitations

• The specific data structure, including column names, row count, and file formats, is not provided in the input.
• The dataset's scope is focused on a specific MRI pulse design algorithm, limiting generalizability to other imaging modalities.
• Recency may be a limitation for applications requiring the latest MRI pulse sequences, as the data is from 2020.

Provenance

Source

Dryad digital repository.

Collection Method

Data generated from iterative numerical simulations using a Bloch equation simulator and subsequent human brain MRI experiments.

Freshness

Last updated on 2020-06-24.