You should not use either T1.mgz as that has been highly processed for
other purposes. The brainmask has also been processed, skull stripped
and bias correction. I have not looked at what has to happen to get the
most correlation between the methods; they are different methods and are
supposed to give different results (we hope that samseg is an
improvement on the aseg). I recommend using the raw input when
specifying recon.
On 3/14/2023 3:26 PM, Giulio Siracusano wrote:
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Dear Experts,
I'm trying to understand what is the best input choice for running
SAMSEG --recon in order to have the closest results as possible when
compared against ASEG after executing (separately) an instance of
recon-all all (and the raw input files in NIFTI format).
I'm very well aware that ASEG and SAMSEG are different methods.
I'm using the aseg.stats file as a results of the recon-all all
command (here renamed as aseg.recon-all.stats for an easier
identification). These stats should be my reference.
Currently I've run the samseg command using the following input variants:
1) raw input file (brain MP-RAGE sequence) converted into a mgz
archive (Raw.mgz).
samseg --t1w ./Raw.mgz --s 002_S_0685_DIRECT --recon --refmode t1w
The corresponding results are attached into (samseg.direct.stats)
2) This time I've used the file T1.mgz which is one of the
intermediate results generated after running recon-all -autorecon 1.
Specifically, this is the output of (mri_normalize
<https://secure-web.cisco.com/1JV3nYNrViePm1qpOtzuMUtCndnVtCut-gp7OyXxNuXIOkpE_qcI5f6sZ_QCwSghG1IFvH334gaAg87lJLYfCvB-5zg8wmDlsw6lAdt8aOlOIPUAjSprkajT7zne-FP-hzGKv9CYvWmcSS9XIenkvKBhlfbO8vOv-ei30mFEGRIZaagYtK1Cyf9wmm4QF6GEj7bEzNVr-YBpfnGSNYSLBmufOWzHUZ-r1QCtztrC9tGdBWY2qatrd7cfd8q57QFqlCEFUVwIesthj1klkWBKBIVP9AjfVSX4ZriNvoJLsVcZ6fSYSPrEW5jpjoBoeTUkDy39-cD7pRoNjCcQMll36FQ/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2Fmri_normalize>
-g 1 -mprage nu.mgz T1.mgz).
samseg --t1w ./T1W/T1.mgz --s 002_S_0685_DIRECT_T1W --recon --refmode t1w
The corresponding samseg.stats file is attached and called
(samseg.direct.t1.stats).
3) this time I've used the file brainmask.mgz which is the last
intermediate result generated after running recon-all -autorecon 1.
Specifically, this is the output of mri_watershed
<https://secure-web.cisco.com/1DjG5BDGTEbHYOWKmd4lc63SOmX8IrmziV9_NRWhpCskwO6lXP_OANTKjLP4P7zNcWyFmHcUAzXkrwvHQHxjel7Kt6VWmoFp0Dec-s6MAlL-nBlLBeauEFL4752dC7HNmXyvpFp8GB9mROITqzNZ0ZMNc5G-lQL2FfUV5IGX-p1DHRNN5Vw7G8qdIAeHIJYRhKRyuEqIzZ0afOXOYp79zF4m6WaEvzjf_-MVMKRTIk65x00-gMPz3jln6JODEdkkvNPc1Vad_tMdDHjoDPvBUPDKPPmc3p840hpjbk-e2W_eYsL1dczzFZsnkSX25piGNbpcwFN_z2Y_fei_T89237Q/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2Fmri_watershed>.
samseg --t1w ./brainmask.mgz --s 002_S_0685_DIRECT_BRAIN --recon
--refmode t1w
The corresponding samseg.stats file is attached and called
(samseg.brain.stats).
I've noticed that the SAMSEG stats file (samseg.brain.stats) as
obtained when using the brainmask.mgz as input file is the closest
with the ASEG statistics (aseg.recon-all.stats).
I also observe that the unknown volume is the lowest (# Measure
Unknown, 5329.102436, mm^3) when using brainmask.mgz as input for
SAMSEG, whereas is higher (Measure Unknown, 325302.894793, mm^3) when
using T1.mgz as input file and is the highest (Measure Unknown,
946924.354060, mm^3) for the raw input.
I know that for running recon-all we use the raw input files (for
example, in NIFTI format),
but I wanted to know what is the best possible configuration for
SAMSEG in terms of input file in order to have the closest match
between SAMSEG and ASEG statistics.
Could it be possible to use the intermediate result T1.mgz or
brainmask.mgz as input file for running samseg command?
Is it a technically correct procedure?
Do we need to use only the raw data as input for running samseg
--recon command?
Hope this is clear
Regards
GS
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