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It is an important research question to improve the denoising methods in `tedana` to provide the user with the most reliable output data to use in their fMRI analyses. This milestone will close when the codebase is stable enough to integrate novel methods into `tedana`...and that happens!
No due date•13/15 issues closedWe will grow the number of users of the project if `tedana` can be used natively through `fmriPrep`. At the moment it is difficult for users to either create the optimal combination or use the `tedana` denoising techniques. Some of the work is not required at this repository - there are updates to `fmriPrep` that need to be integrated, but other changes will need to happen here (for example making sure the outputs are BIDS compliant). This milestone will close when the denoising steps of `tedana` are stable enough to integrate into `fmriPrep` and the `fmriPrep` project is updated to process ME-EPI scans.
No due date•10/10 issues closedWe will grow the number of users of the project if `tedana` can be used natively through AFNI. At the moment an older version of the code is shipped with AFNI and used in their `afni_proc` workflow. This milestone will close when `tedana` is stable enough to integrate into `afni_proc.py` via `pip install tedana` rather than maintaining the alternative version that is currently used.
No due date•1/1 issues closedIn order to reach our ultimate goal of bringing in functionality developed by new contributors, we need to maintain a healthy community. A healthy community is also one in which the maintainers are happy and not overworked, and one in which the users feel empowered to contributed back to the project. This milestone will probably never close, but will track issues related to supporting and building the `tedana` community.
No due date•7/7 issues closedIn order to build and maintain confidence in the `tedana` processing the software must provide back to the user enough information on what methods were applied to the data and which specific selection criteria were used in making denoising decisions. Additionally it is necessary that each analysis can be reproduced and therefore the non-deterministic steps must be able to be repeated identically by running the code with a fixed random seed. Finally, transparent and reproducible processing will permit clear reporting of the ME-EPI results in published studies.<br><br> This milestone will close when an analysis can be reproduced by an independent researcher who has access to the same data, and when the internal decision making process for which components are selected is made accessible to the end user.
No due date•32/33 issues closed- No due date•4/4 issues closed
First minor release of tedana. Set roughly 3 months after 0.0.9 release.
Overdue by 4 year(s)•Due by May 10, 2021•16/17 issues closed