PulPy: A Python Toolkit for MRI RF and Gradient Pulse Design
DOI:
https://doi.org/10.31224/3820Keywords:
Magnetic Resonance ImagingAbstract
We present PulPy (Pulses in Python), an extensive set of open-source, Python-based tools for magnetic resonance imaging (MRI) radiofrequency (RF) and gradient pulse design. PulPy is a Python package containing implementations of a wide range of commonly used RF and gradient pulse design tools. Our implemented functions for RF pulse design include advanced Shinnar-LeRoux (SLR), multiband, adiabatic, optimal control, B1+-selective and small-tip parallel transmission (pTx) designers. Gradient waveform design functionality is included, providing the ability to design and optimize readout or excitation k-space trajectories [@Pauly1989]. Other useful tools such as vendor-specific waveform input/output, Bloch equation simulators, abstracted linear operators, and pulse reshaping functions are included. This toolbox builds on the RF tools introduced previously in the SigPy.RF Python software package [@Martin2020a]. The current toolbox continues to leverage SigPy’s existing capabilities for GPU computation, iterative optimization, and powerful abstractions for linear operators and applications [@Ong2019]. The table below shows an outline of the implemented functions.
Preliminary development of this toolbox was presented in reference [@Martin2020a]. The pulse design tools were initially implemented as a sub-package in the SigPy Python package for signal processing and image reconstruction [@Ong2019]. PulPy migrates those tools into a pulse design specific package, with SigPy as an external dependency. PulPy has been streamlined and expanded to include a larger collection of RF and gradient pulse design methods from the literature, as well as additional utility tools for I/O, pulse reshaping, and experimental B1+-selective pulse design algorithms. The toolbox has proved useful for prototyping novel pulse design algorithms, enabling the publication of Reference [@Martin2022] by the authors and several works from other groups [@Shin2021, @Wu2023]. Figure 1 shows an example of RF and gradient waveforms produced by PulPy.
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Copyright (c) 2024 Jonathan Martin, Heng Sun, Madison Albert, Kevin Johnson, William Grissom
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