Dear experts,
We are working with a large MRI dataset
(FLAIR, T1) and we are performing SAMSEG pipeline to estimate
lesion volumes. We computed the registration between the two
input images and the resampling as advised in the SAMSEG page
(mri_coreg and mri_vol2vol) which worked
perfectly. However, when we do the visual chek on the
segmentation after running SAMSEG, it is completely wrong for
some subjects. By looking at corresponding
mode01_bias_corrected.mgz and mode02_bias_corrected.mgz
images, they are too cropped (centered on the cerebellum)
compared to the original ones (3D_T1 .nii.gz and
3D_FLAIR.nii.gz). We also noticed a « RuntimeWarning: invalid
value encountered in true_divide » during the burn-in phase
(in the GMM.py code).
Do you have any clue of what is happening
with this cropping (can it be linked to the bias field
estimation ?) and how we can correct it ?
Thanks for your help and I can provide some
screenshots of the cropped images to help visualize the issue.
Best,
Achille Teillac