You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Katie Bottenhorn, NBCLab, Florida International University
Eneko Uruñuela, BCBL
Stefano Moia, NIMH
Javier Gonzalez-Castillo, NIMH
Brief description of what was accomplished with this project
The tedana package is part of the ME-ICA pipeline, performing TE-dependent analysis of multi-echo functional magnetic resonance imaging (fMRI) data. TE-dependent analysis (tedana) is a Python module for denoising multi-echo functional magnetic resonance imaging (fMRI) data.
Upon completion, tedana generates a complex set of outputs that need to be inspected in detail prior to moving forward with any analyses. This project tries to generate a set of dynamic reports that help users inspect their results.
Dynamic Reports for tedana
Brief description of what was accomplished with this project
The tedana package is part of the ME-ICA pipeline, performing TE-dependent analysis of multi-echo functional magnetic resonance imaging (fMRI) data. TE-dependent analysis (tedana) is a Python module for denoising multi-echo functional magnetic resonance imaging (fMRI) data.
Upon completion, tedana generates a complex set of outputs that need to be inspected in detail prior to moving forward with any analyses. This project tries to generate a set of dynamic reports that help users inspect their results.
Resources
https://github.com/ME-ICA/tedana
The text was updated successfully, but these errors were encountered: