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Hi Stefano,
thanks a lot for advice on t2 intensity pattern. I ran couple of cases and I clearly see an improvement. I do not need to reduce threshold at all to get better results. Although the number of FN dropped by roughly 1/2, there are still quite a lot of them. For example, the lesion which I sent in my first email is still left behind. I am happy to send you that particular case. May I ask you for instructions, where to upload it?
Thanks,
Martin
On Sun, Aug 14, 2022 at 10:52 PM Cerri, Stefano SCERRI@mgh.harvard.edu wrote:
Hi Martin,
Can you try to remove the lesion intensity constraint on the T2 data (i.e., by modifying your command with --lesion-mask-pattern 0 1 0) for a couple of cases and let us know if it helps?
If not, would you be able to share with us one case where it fails?
FYI: you can save a lesion probability map directly by using the flag "--save-posteriors Lesions" so you don't need to try different thresholds.
Thanks, Stefano
Subject: [Freesurfer] Large number of false negative MS lesions in SAMSEG Date: Sun, 14 Aug 2022 20:54:50 +0200 From: Martin Kavec martin.kavec@gmail.com martin.kavec@gmail.com Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu freesurfer@nmr.mgh.harvard.edu To: Freesurfer mailing list freesurfer@nmr.mgh.harvard.edu freesurfer@nmr.mgh.harvard.edu
External Email - Use CautionHello,
I am testing SAMSEG on my group of MS patients. Unfortunately, even when dropping threshold to 0.005 I have large number of false negative lesions left behind by SAMSEG (80% in about 75 cases I tried), which are clearly visible lesions. I ran/checked registration between inputs, which is typically very good to excellent. Images are all 3D acquisitions , mprage, flair, and t2 with ~1 mm3 isotropic voxel. Here is the command, which I ran:
run_samseg --input mprage_reg.nii.gz flair.nii.gz t2_reg.nii.gz --pallidum-separate --lesion --lesion-mask-pattern 0 1 1 --threshold 0.005 --output samseg_threshold_0.005
and example of the lesion in occipital white matter in sagittal and axial orientations.
[image: image.png] [image: image.png]
I would very much appreciate any leads as to how to improve the segmentation.
Thanks,
Martin
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