Image and mask affines are not similar enough

[duddb3]

What happened?

I have a single T2w image and a single BOLD run for a newborn. I have passed the T2w thru BIBSNET which completed successfully. When I attempt to run nibabies, the pipeline crashes early on. The node that fails reports that the "in_file" input is undefined, which seems strange.

What command did you use?

docker run --rm -v C:\bids_directory:/tmp/datadir -v C:\freesurfer_directory:/tmp/FSlicense nipreps/nibabies:25.0.2 datadir datadir/derivatives participant -w work/ --participant-label 1003 --fs-license-file /FSlicense/freesurfer-license.txt --derivatives datadir/derivatives/sourcedata/bibsnet --surface-recon-method mcribs --project-goodvoxels --cifti-output 91k --stop-on-first-crash -v

What version of NiBabies are you using?

nipreps/nibabies:25.0.2

Relevant log output

Node: nibabies_25_0_wf.single_subject_sub-1003_wf.infant_single_t2w_fit_wf.apply_mask
Working directory: /tmp/work/nibabies_25_0_wf/single_subject_sub-1003_wf/infant_single_t2w_fit_wf/apply_mask

Node inputs:

in_file = <undefined>
in_mask = /tmp/datadir/derivatives/sourcedata/bibsnet/sub-1003/anat/sub-1003_space-T2w_desc-brain_mask.nii.gz
threshold = 0.5

Traceback (most recent call last):
  File "/opt/conda/envs/nibabies/lib/python3.11/site-packages/nipype/pipeline/plugins/multiproc.py", line 67, in run_node
    result["result"] = node.run(updatehash=updatehash)
                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/nibabies/lib/python3.11/site-packages/nipype/pipeline/engine/nodes.py", line 525, in run
    result = self._run_interface(execute=True)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/nibabies/lib/python3.11/site-packages/nipype/pipeline/engine/nodes.py", line 643, in _run_interface
    return self._run_command(execute)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/nibabies/lib/python3.11/site-packages/nipype/pipeline/engine/nodes.py", line 769, in _run_command
    raise NodeExecutionError(msg)
nipype.pipeline.engine.nodes.NodeExecutionError: Exception raised while executing Node apply_mask.

Traceback:
	Traceback (most recent call last):
	  File "/opt/conda/envs/nibabies/lib/python3.11/site-packages/nipype/interfaces/base/core.py", line 401, in run
	    runtime = self._run_interface(runtime)
	              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
	  File "/opt/conda/envs/nibabies/lib/python3.11/site-packages/niworkflows/interfaces/nibabel.py", line 78, in _run_interface
	    raise ValueError('Image and mask affines are not similar enough.')
	ValueError: Image and mask affines are not similar enough.

Add any additional information or context about the problem here.

The BIBSNET output IS in alignment with original T2w image, although the affines are slightly different (~1E-6 or less). I have tried replacing the BIBSNET output headers with the headers from the original T2w image, but I encounter the same error when running nibabies.

[mgxd]

There seems to be some discrepancy with BIBSNet ingestion - related issue #458 and proposed fix #459

@duddb3 is there any discrepancy in orientation between your raw data and bibsnet derivatives? Would you mind trying out the proposed fix and see if it works for you?

[duddb3]

Thanks for the quick response @mgxd!

I pulled the nipreps/nibabies:derivatives-no-preproc image and ran that with the same options listed above but I am getting the same error message.

edit to clarify: I have also made sure there is no discrepancy between the orientation information in my raw dataset (i.e. in bids_directory/sub-1003/anat/sub-1003_T2w.nii.gz) and the bibsnet derivatives (i.e., in bids_directory/derivatives/sourcedata/bibsnet/sub-1003/anat/sub-1003_space-T2w_desc-brain_mask.nii.gz)

[mgxd]

hi @duddb3 sorry for the delay - I just pushed a change to nipreps/nibabies:derivatives-no-preproc that might fix the problem you are seeing, though it is hard for me to verify without having some failing data. If you wouldn't mind, could you give it a go and report back?

[duddb3]

I don't know how you figured it out, but it works! Thanks for the support @mgxd