README.md

tSNR

Calculates the temporal SNR (tSNR) and signal fluctuation to noise ratio (SFNR) of a 4D NIFTI containing time series images. Scripts in this repository are for building a processing gear in Flywheel.

• Gear input:
  • 4D NIFTI
• Gear configuration options:
  • Mask threshold
  • Number of discarded volumes
  • Size of central ROI
• Gear outputs:
  • tSNR map *_tsnr.nii.gz, SFNR map *_sfnr.nii.gz
  • Plot of the temporal drift of mean signal within ROI *_mean_signal.png, plot of the temporal drift of center of mass *_cm_drift.png, plot of Weisskoff analysis (radius of decorrelation) *_rdc.png
  • JSON file *_results.json containing statistic results, e.g. mean tSNR, SFNR in ROI
  • Other intermediate results

The script tsnr.py can also be executed seperately to generate tSNR maps on 4D NIFTIs containing time series images:

python tsnr.py [-o OUTBASE] [-d DISCARD_VOL] [-f BET_FRAC] [-r ROI_SIZE] infile

Dependencies include AFNI, NumPy, SciPy, NiBabel.

Reference: Friedman and Glover, 2006, Report on a multicenter fMRI quality assurance protocol.