SMART MRS : A Simulated MEGA-PRESS Artifacts Toolbox for GABA-edited MRS
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Purpose
To create a Python-based toolbox to simulate commonly occurring artifacts for single voxel Gamma-Aminobutyric Acid (GABA)-edited Magnetic Resonance Spectroscopy (MRS) data.
Methods
The toolbox was designed to maximize user flexibility and contains artifact, applied, input/output (I/O), and support functions. The artifact functions can produce spurious echoes, eddy currents, nuisance peaks, line broadening, baseline contamination, linear frequency drifts, and frequency and phase shift artifacts. Applied functions combine or apply specific parameter values to produce recognizable effects such as lipid peak and motion contamination. I/O and support functions provide additional functionality to accommodate different kinds of input data (MATLAB FID-A .mat files, nifti-mrs files), which vary by domain (time vs. frequency), collection type (edited vs. non-edited) and scale.
Results
Users may provide some or all of the required artifact function parameter values which will result in artifacts of different appearances. Visual assessment confirms the resemblance of simulated compared to in vivo produced artifacts.
Conclusion
Our pip installable Python artifact simulated toolbox SMART_MRS is meant to enhance the diversity and quality of existing simulated edited-MRS data and is complementary to existing MRS simulation software.
