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Dear FreeSurfer Developers,

I hope this email finds you well!

I am using fMRIprep to do pre-processing. The fMRIprep combines methodology from AFNI, ANTs, Freesurfer, FSL, and Mindboggle to do preprocessing.

 An error was reported while running the fMRIprep. It seems that it was due to the structural data and it was about the registration by FreeSurfer. But I am new in the neuroimaging area and not very sure about what the error actually is about. 

I asked the fmriprep team in neurostars (https://neurostars.org/t/fmriprep-error-makeisotropic-warning-not-different-enough-wont-reslice/29839/5) and they are also not sure about this and recommended to ask the FreeSurfer. Although I am not sure if the FreeSurfer in fmriprep is what you also work with, I would like to ask and would really appreciate it if you could help explain what error it is. Thanks you so much!

The error is attached below. Please let me know if you have any questions or if more information is needed!

Fmriprep error: makeIsotropic WARNING: not different enough, won't reslice! Summary of what happened: Hi, I am running fmriprep and getting the following error. I would really appreciate any help! Please let me know if more information should be provided! Thanks so much, tengwen Command used (and if a helper script was used, a link to the helper script or the command generated): fmriprep-docker /Users/Desktop/WL_fMRI/data/BIDS /Users/Desktop/WL_fMRI/data/derivatives/fmriprep participant --participant-label sub-WLfMRI035 --fs-license-file /Users/Desktop/WL_fMRI/licen... neurostars.org

The Error is: 

Cmdline:

        mri_robust_register --satit --iscale --lta /tmp/work/fmriprep_23_2_wf/sub_WLfMRI033_wf/anat_fit_wf/surface_recon_wf/fsnative2t1w_xfm/T1_robustreg.lta --mov /out/sourcedata/freesurfer/sub-WLfMRI033/mri/T1.mgz --dst /tmp/work/fmriprep_23_2_wf/sub_WLfMRI033_wf/anat_fit_wf/anat_template_wf/denoise/mapflow/_denoise0/sub-WLfMRI033_ses-Session1_T1w_noise_corrected.nii.gz

Stdout:

        7.3.2

 

        --satit: Will iterate with different SAT to ensure outliers below wlimit!

        --iscale: Enabling intensity scaling!

        --lta: Output transform as /tmp/work/fmriprep_23_2_wf/sub_WLfMRI033_wf/anat_fit_wf/surface_recon_wf/fsnative2t1w_xfm/T1_robustreg.lta . 

        --mov: Using /out/sourcedata/freesurfer/sub-WLfMRI033/mri/T1.mgz as movable/source volume.

        --dst: Using /tmp/work/fmriprep_23_2_wf/sub_WLfMRI033_wf/anat_fit_wf/anat_template_wf/denoise/mapflow/_denoise0/sub-WLfMRI033_ses-Session1_T1w_noise_corrected.nii.gz as target volume.

 

        reading source '/out/sourcedata/freesurfer/sub-WLfMRI033/mri/T1.mgz'...

        reading target '/tmp/work/fmriprep_23_2_wf/sub_WLfMRI033_wf/anat_fit_wf/anat_template_wf/denoise/mapflow/_denoise0/sub-WLfMRI033_ses-Session1_T1w_noise_corrected.nii.gz'...

 

        Registration::setSourceAndTarget(MRI s, MRI t, keeptype = TRUE )

          Type Source : 0  Type Target : 3  ensure both FLOAT (3)

          Reordering axes in mov to better fit dst... ( -1 -3 2 )

        Determinant after swap : 1

          Mov: (0.5, 0.5, 0.5)mm  and dim (512, 512, 512)

          Dst: (0.5, 0.5, 0.5)mm  and dim (360, 512, 512)

          Asserting both images: 0.5mm isotropic 

            - reslicing Mov ...

              -- changing data type from 0 to 3 (noscale = 0)...

            - reslicing Dst ...

              -- Original : (0.5, 0.5, 0.5)mm and (360, 512, 512) voxels.

              -- Resampled: (0.5, 0.5, 0.5)mm and (512, 512, 512) voxels.

              -- Reslicing using cubic bspline 

        MRItoBSpline degree 3

            - WARNING: trg mri outside_val = 0  but suspected background: -0.00687514

                      If background is black or darkgray, ignore this. If white, pass --whitebgdst

 

 

        Registration::findSaturation 

          - computing centroids 

          - computing initial transform

            -- using translation info

          - Get Gaussian Pyramid Limits ( min size: 16 max size: -1 ) 

          - Build Gaussian Pyramid ( Limits min steps: 0 max steps: 4 ) 

          - Build Gaussian Pyramid ( Limits min steps: 0 max steps: 4 ) 

 

          - Max Resolution used: 3

            -- gpS ( 64 , 64 , 64 )

            -- gpT ( 64 , 64 , 64 )

          - running loop to estimate saturation parameter:

            -- Iteration: 1  trying sat: 16

                min sat: 0 ( -1 ), max sat: 16 ( 0.12101 ), sat diff: 16, (wlimit=0.16)

            -- Iteration: 2  trying sat: 8

                min sat: 8 ( 0.324589 ), max sat: 16 ( 0.12101 ), sat diff: 8, (wlimit=0.16)

            -- Iteration: 3  trying sat: 12

                min sat: 12 ( 0.193726 ), max sat: 16 ( 0.12101 ), sat diff: 4, (wlimit=0.16)

            -- Iteration: 4  trying sat: 14

                min sat: 12 ( 0.193726 ), max sat: 14 ( 0.15173 ), sat diff: 2, (wlimit=0.16)

            -- Iteration: 5  trying sat: 13

                min sat: 13 ( 0.17074 ), max sat: 14 ( 0.15173 ), sat diff: 1, (wlimit=0.16)

            -- Iteration: 6  trying sat: 13.5

          - final SAT: 14 ( it: 6 , weight check 0.15173 <= 0.16 )

 

 

        Registration::computeMultiresRegistration 

          - computing centroids 

          - computing initial transform

            -- using translation info

          - Get Gaussian Pyramid Limits ( min size: 16 max size: -1 ) 

          - initial transform:

        Ti = [ ...

        1.0000000000000                0                0  1.6982521922295 

                      0  1.0000000000000                0 -1.1595074345649 

                      0                0  1.0000000000000 -1.1415599519338 

                      0                0                0  1.0000000000000  ]

 

          - initial iscale:  Ii =1

 

        Resolution: 4  S( 32 32 32 )  T( 32 32 32 )

        Iteration(f): 1

            -- intensity log diff: abs(-0.85599) 

            -- diff. to prev. transform: 1.62699

        Iteration(f): 2

            -- intensity log diff: abs(-0.0720915) 

            -- diff. to prev. transform: 0.761125

        Iteration(f): 3

            -- intensity log diff: abs(-0.00194135) 

            -- diff. to prev. transform: 0.0383579

        Iteration(f): 4

            -- intensity log diff: abs(-0.00123869) 

            -- diff. to prev. transform: 0.0128975

        Iteration(f): 5

            -- intensity log diff: abs(-0.000750416)  <= 0.001  :-)

            -- diff. to prev. transform: 0.00518321  <= 0.01   :-)

 

        Resolution: 3  S( 64 64 64 )  T( 64 64 64 )

        Iteration(f): 1

            -- intensity log diff: abs(0.00702447) 

            -- diff. to prev. transform: 0.977321

        Iteration(f): 2

            -- intensity log diff: abs(9.94659e-05)  <= 0.001  :-)

            -- diff. to prev. transform: 0.0258922

        Iteration(f): 3

            -- intensity log diff: abs(1.21569e-05)  <= 0.001  :-)

            -- diff. to prev. transform: 0.00163623  <= 0.01   :-)

 

        Resolution: 2  S( 128 128 128 )  T( 128 128 128 )

        Iteration(f): 1

            -- intensity log diff: abs(-0.000545933)  <= 0.001  :-)

            -- diff. to prev. transform: 0.356881

        Iteration(f): 2

            -- intensity log diff: abs(-7.53945e-05)  <= 0.001  :-)

            -- diff. to prev. transform: 0.0881187

        Iteration(f): 3

            -- intensity log diff: abs(-5.00529e-05)  <= 0.001  :-)

            -- diff. to prev. transform: 0.0253314

        Iteration(f): 4

            -- intensity log diff: abs(-2.0764e-05)  <= 0.001  :-)

            -- diff. to prev. transform: 0.00744419  <= 0.01   :-)

 

        Resolution: 1  S( 256 256 256 )  T( 256 256 256 )

        Iteration(f): 1

            -- intensity log diff: abs(0.00127177) 

            -- diff. to prev. transform: 0.268975

        Iteration(f): 2

            -- intensity log diff: abs(0.000348898)  <= 0.001  :-)

            -- diff. to prev. transform: 0.0666025

        Iteration(f): 3

            -- intensity log diff: abs(8.4156e-05)  <= 0.001  :-)

            -- diff. to prev. transform: 0.016444

        Iteration(f): 4

            -- intensity log diff: abs(2.77798e-05)  <= 0.001  :-)

            -- diff. to prev. transform: 0.00492133  <= 0.01   :-)

 

        Resolution: 0  S( 512 512 512 )  T( 512 512 512 )

        Iteration(f): 1

            -- WARNING: mem usage large: 4668.08Mb mem + 6 MRI

                  Maybe use --subsample <int> 

Stderr:

        makeIsotropic WARNING: not different enough, won't reslice!

        Killed

Traceback:

        Traceback (most recent call last):

          File "/opt/conda/envs/fmriprep/lib/python3.10/site-packages/nipype/interfaces/base/core.py", line 398, in run

            runtime = self._post_run_hook(runtime)

          File "/opt/conda/envs/fmriprep/lib/python3.10/site-packages/niworkflows/interfaces/freesurfer.py", line 248, in _post_run_hook

            fix_lta_length(lta_file)

          File "/opt/conda/envs/fmriprep/lib/python3.10/site-packages/niworkflows/interfaces/freesurfer.py", line 399, in fix_lta_length

            lines = Path(lta_file).read_text().splitlines(keepends=True)

          File "/opt/conda/envs/fmriprep/lib/python3.10/pathlib.py", line 1134, in read_text

            with self.open(mode='r', encoding=encoding, errors=errors) as f:

          File "/opt/conda/envs/fmriprep/lib/python3.10/pathlib.py", line 1119, in open

            return self._accessor.open(self, mode, buffering, encoding, errors,

        FileNotFoundError: [Errno 2] No such file or directory: '/tmp/work/fmriprep_23_2_wf/sub_WLfMRI033_wf/anat_fit_wf/surface_recon_wf/fsnative2t1w_xfm/T1_robustreg.lta'

Best,

Tengwen

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