Hello,
I am pretty new to the spinal cord toolbox and MRI data analysis. I tried running the propseg command for the t2 weighted data and gets error related to the dimensions of the data. Please see the terminal output.
pawan_0210@DESKTOP-MDS0OFU:/mnt/c/sct_course_london20/Test_Data/Data/t2$ sct_propseg -i 1008_T10-L2_Trans.nii.gz -c t2 -
qc ~/qc-1008_sagView–
Spinal Cord Toolbox (5.7)sct_propseg -i 1008_T10-L2_Trans.nii.gz -c t2 -qc /home/pawan_0210/qc-1008_sagView
Creating temporary folder (/tmp/sct-20220812171336.666343-propseg-qm8r0h8h)
Creating temporary folder (/tmp/sct-20220812171336.850785-label_vertebrae-4ehac8jx)
Creating temporary folder (/tmp/sct-20220812171336.852620-36c5flql)
Remove temporary files…
rm -rf /tmp/sct-20220812171336.852620-36c5flql
/home/pawan_0210/sct_5.7/bin/isct_propseg -t t2 -o /tmp/sct-20220812171336.666343-propseg-qm8r0h8h -verbose -i /mnt/c/sct_course_london20/Test_Data/Data/t2/1008_T10-L2_Trans.nii.gz -init-centerline /tmp/sct-20220812171336.850785-label_vertebrae-4ehac8jx/centerline_optic.nii.gz -centerline-binary # in /mnt/c/sct_course_london20/Test_Data/Data/t2
mv /tmp/sct-20220812171336.666343-propseg-qm8r0h8h/1008_T10-L2_Trans_seg.nii.gz ./1008_T10-L2_Trans_seg.nii.gz
mv /tmp/sct-20220812171336.666343-propseg-qm8r0h8h/1008_T10-L2_Trans_centerline.nii.gz ./1008_T10-L2_Trans_centerline.nii.gzCheck consistency of segmentation…
Creating temporary folder (/tmp/sct-20220812171407.929757-propseg-c3u2clsv)
/tmp/sct-20220812171407.929757-propseg-c3u2clsv/tmp.segmentation.nii.gz
/tmp/sct-20220812171407.929757-propseg-c3u2clsv/tmp.centerline.nii.gzGet data dimensions…
/tmp/sct-20220812171407.929757-propseg-c3u2clsv/tmp.segmentation_RPI_c.nii.gz
rm -rf /tmp/sct-20220812171407.929757-propseg-c3u2clsv
Copy header input → output(s) to make sure qform is the same.
File /mnt/c/sct_course_london20/Test_Data/Data/t2/1008_T10-L2_Trans_seg.nii.gz already exists. Will overwrite it.
File /mnt/c/sct_course_london20/Test_Data/Data/t2/1008_T10-L2_Trans_centerline.nii.gz already exists. Will overwrite it.*** Generate Quality Control (QC) html report ***
Resample images to 0.6x0.6 mm
Traceback (most recent call last):
File “/home/pawan_0210/sct_5.7/spinalcordtoolbox/scripts/sct_propseg.py”, line 699, in
main(sys.argv[1:])
File “/home/pawan_0210/sct_5.7/spinalcordtoolbox/scripts/sct_propseg.py”, line 693, in main
dataset=qc_dataset, subject=qc_subject, process=‘sct_propseg’)
File “/home/pawan_0210/sct_5.7/spinalcordtoolbox/reports/qc.py”, line 780, in generate_qc
qcslice_type = qcslice.Axial([Image(fname_in1), Image(fname_seg)])
File “/home/pawan_0210/sct_5.7/spinalcordtoolbox/reports/slice.py”, line 58, in init
img_r = self._resample_slicewise(img, p_resample, type_img=type_img, image_ref=image_ref)
File “/home/pawan_0210/sct_5.7/spinalcordtoolbox/reports/slice.py”, line 350, in _resample_slicewise
nii_r = resample_nib(nii, image_dest=nii_ref, interpolation=dict_interp[type_img])
File “/home/pawan_0210/sct_5.7/spinalcordtoolbox/resampling.py”, line 116, in resample_nib
img, to_vox_map=reference, order=dict_interp[interpolation], mode=mode, cval=0.0, out_class=None)
File “/home/pawan_0210/sct_5.7/python/envs/venv_sct/lib/python3.7/site-packages/nibabel/processing.py”, line 172, in resample_from_to
to_vox2from_vox = npl.inv(a_from_affine).dot(a_to_affine)
ValueError: shapes (4,4) and (5,5) not aligned: 4 (dim 1) != 5 (dim 0)
Any idea why is this happening. As I mentioned, I am new to this type of work and may not have understanding related to the data structure to be used for the spinalcord toolbox.
Thank you,
Pawan
