tedana.model.combine¶

Functions to optimally combine data across echoes.

Functions

make_optcom(data, t2s, tes, mask, combmode) Optimally combine BOLD data across TEs.

make_optcom(data, t2s, tes, mask, combmode, verbose=True)[source]¶

Optimally combine BOLD data across TEs.

Parameters:	data ((S x E x T) `numpy.ndarray`) – Concatenated BOLD data. t2 ((S,) `numpy.ndarray`) – Estimated T2* values. tes (`numpy.ndarray`) – Array of TEs, in seconds. mask ((S,) `numpy.ndarray`) – Brain mask in 3D array. combmode (`str`) – How to combine data. Either ‘ste’ or ‘t2s’. verbose (`bool`, optional) – Whether to print status updates
Returns:	combined – Optimally combined data.
Return type:	(S x T) `numpy.ndarray`

Notes

Estimate voxel- and TE-specific weights based on estimated $T_2^*$ :

$w(T_2^*)_n = \frac{TE_n * exp(\frac{-TE} {T_{2(est)}^*})}{\sum TE_n * exp(\frac{-TE}{T_{2(est)}^*})}$
Perform weighted average per voxel and TR across TEs based on weights estimated in the previous step.