tedana.workflows.t2smap_workflow

t2smap_workflow(data, tes, out_dir='.', mask=None, prefix='', convention='bids', masktype=['dropout'], fittype='loglin', fitmode='all', combmode='t2s', debug=False, quiet=False, t2smap_command=None)[source]

Estimate T2 and S0, and optimally combine data across TEs.

Please remember to cite DuPre et al.[1].

Parameters:

  • data (str or list of str) – Either a single z-concatenated file (single-entry list or str) or a list of echo-specific files, in ascending order.

  • tes (list) – List of echo times associated with data in milliseconds.

  • out_dir (str, optional) – Output directory.

  • mask (str, optional) – Binary mask of voxels to include in TE Dependent ANAlysis. Must be spatially aligned with data.

  • masktype (list with ‘dropout’ and/or ‘decay’ or None, optional) – Method(s) by which to define the adaptive mask. Default is [“dropout”].

  • fittype ({‘loglin’, ‘curvefit’}, optional) – Monoexponential fitting method. ‘loglin’ means to use the the default linear fit to the log of the data. ‘curvefit’ means to use a monoexponential fit to the raw data, which is slightly slower but may be more accurate.

  • fitmode ({‘all’, ‘ts’}, optional) – Monoexponential model fitting scheme. ‘all’ means that the model is fit, per voxel, across all timepoints. ‘ts’ means that the model is fit, per voxel and per timepoint. Default is ‘all’.

  • combmode ({‘t2s’, ‘paid’}, optional) – Combination scheme for TEs: ‘t2s’ (Posse 1999, default), ‘paid’ (Poser).

  • t2smap_command (str, optional) – The command used to run t2smap. Default is None.

Other Parameters:

  • debug (bool, optional) – Whether to run in debugging mode or not. Default is False.

  • quiet (bool, optional) – If True, suppress logging/printing of messages. Default is False.

Notes

This workflow writes out several files, which are described below:

Filename

Content

T2starmap.nii.gz

Estimated T2* 3D map or 4D timeseries. Will be a 3D map if fitmode is ‘all’ and a 4D timeseries if it is ‘ts’.

S0map.nii.gz

S0 3D map or 4D timeseries.

desc-limited_T2starmap.nii.gz

Limited T2* map/timeseries. The difference between the limited and full maps is that, for voxels affected by dropout where only one echo contains good data, the full map uses the T2* estimate from the first two echos, while the limited map will have a NaN.

desc-limited_S0map.nii.gz

Limited S0 map/timeseries. The difference between the limited and full maps is that, for voxels affected by dropout where only one echo contains good data, the full map uses the S0 estimate from the first two echos, while the limited map will have a NaN.

desc-optcom_bold.nii.gz

Optimally combined timeseries.

References