Dual-echo time series are not currently combined as, to the best of my understanding, the current literature does not recommend a combination method for dual-echo acquisitions.
Instead, dual-echo acquisitions generally follow the Bright and Murphy denoising strategy, in which the first echo is used as a regressor time series.
It would not be possible to combine dual-echo time series using the optimal combination method advocated by Kundu and colleagues, as we require at least three echos to map the T2* decay.
Is there other relevant literature you can recommend in which dual-echo time series are used to generate an optimal combination ? Happy to be pointed to other combination strategies !
Thanks for sharing these ! I’m less familiar with the dual-echo literature, so it’s great to see this has been addressed. Do you have a python implementation of this combination method ?
No sorry, just Matlab. If you’re interested in the code, I can ask if the person that provided it is willing to share.
By the way, the Halai et al. paper (the latter one above), shows that plain averaging (linear summation) of the two images basically works just as well the CNR method for dual-echo data, and this is also what several studies I know have done, e.g. http://www.jneurosci.org/content/36/5/1490.short. So the CNR method might not be worth the trouble, especially if you want to use independent data of your task data to calculate tSNR (you should, of course…), which requires additional measurement time.
I’m running into the same situation here. Should I just add the raw files of the two echos and then feed it into fmriprep as if it is single echo? Or should it be done in some later stages?