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nipreps / dmriprep

dMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse dMRI data. The transparent workflow dispenses of manual intervention, thereby ensuring the reproducibility of the results.
https://www.nipreps.org/dmriprep
Apache License 2.0
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FIX: Correctly check SDCFlows registry of ``IntendedFor`` files #141

Closed oesteban closed 3 years ago

oesteban commented 3 years ago

Follows up on #140

EDIT 12/17/2020 --

Summary

This PR explores the new SDCFlows API to apply fieldmaps. Although the control over the available fieldmaps is almost none and many issues are still to be solved, this is a second step towards the integration.

Now, the CircleCI reports contain SDC results reportlets for ds001771 - one of them looks decent, the other needs some investigation.

This dataset contains two fake _fieldmap images - these are the two with the weird mask (the problem is that SDCFlows expects a magnitude image, but receives an EPI, because these are fake fieldmaps derived from the TOPUP solution).

oesteban commented 3 years ago

Failing for the same root cause of nipreps/sdcflows#158 (broken dependency of scikit-image).

josephmje commented 3 years ago

This dataset contains two fake _fieldmap images - these are the two with the weird mask (the problem is that SDCFlows expects a magnitude image, but receives an EPI, because these are fake fieldmaps derived from the TOPUP solution).

Ha! I tested this out earlier and was wondering why the fieldmaps looked the same as the TOPUP solution.

oesteban commented 3 years ago

Ha! I tested this out earlier and was wondering why the fieldmaps looked the same as the TOPUP solution.

Wonder no more. I think this is something that @edickie spotted a long while ago.