Re: [Freesurfer] SAMSEG "lesion" (Illegal instruction) ~ running VM_67

[Cerri, Stefano]

Hi Randy,

Your run_samseg syntax is correct and yes, the "lesion" version of SAMSEG 
requires Tensorflow.

The "illegal instruction" error is most probably related to an incompatible 
version of Tensorflow with your CPU instruction set. You should be able to 
replicate the error by typing:


  1.  fspython

  1.  import tensorflow

Would you be able to run SAMSEG lesion on another host machine (possibly a 
relatively new one) and let us know if the error persists?

Best,
Stefano

Dear R,
Yes, I have tried to run "samseg_run" from the command line (I've repeated my 
syntax below).? I have looked both under the directory where the command ran 
that produced the ?Illegal instruction? error.? No crash file (a logfile?) or a 
"core" file were written.? I also looked?/var/crash but that folder was empty 
too.

As I mentioned, I'm a LINUX novice.? I'm even more of a novice with regard to 
Python. However, I did take a quick at the code looking for any mention of 
tensorflow, and have copied the python script text as it exists below.? I have 
highlighted the only mention of tensorflow below.? Does this look like you 
expect it?
Has tensorflow actually been incorporated into the VM???
Note that I have been able to successfully run Samseg without the --lesion flag 
and the process works just fine (about 20min runtime, aseg looks just fine in 
Freeview)
Again, thanks for any guidance you can provide.
-Randy
xxx

#!/usr/bin/env python
import osimport sysimport jsonimport scipy.ioimport freesurfer as fsimport 
freesurfer.samseg as samseg

# -- Parse Command Line Arguments --
parser = fs.utils.ArgumentParser()
default_threads = int(os.environ.get('OMP_NUM_THREADS', 1))
# requiredparser.add_argument('-o', '--output', metavar='DIR', 
dest='outputDirectory', help='Output directory.', 
required=True)parser.add_argument('-i', '--input', nargs='+', action='extend', 
metavar='FILE', dest='inputFileNames', help='Input image(s).', required=True)# 
optional processing optionsparser.add_argument('-m', '--mode', nargs='+', 
help='Output basenames for the input image 
mode.')parser.add_argument('--threads', type=int, default=default_threads, 
help='Number of threads to use. Defaults to current OMP_NUM_THREADS or 
1.')parser.add_argument('--reg-only', action='store_true', default=False, 
help='Only perform initial affine registration.')parser.add_argument('-r', 
'--reg', metavar='FILE', help='Skip initial affine registration and read 
transform from file.')parser.add_argument('--init-reg', metavar='FILE', 
help='Initial affine registration.')parser.add_argument('-a', '--atlas', 
metavar='DIR', help='Point to an alternative atlas 
directory.')parser.add_argument('--gmm', metav
 ar='FILE', help='Point to an alternative GMM 
file.')parser.add_argument('--ignore-unknown', action='store_true', 
help='Ignore final priors corresponding to unknown 
class.')parser.add_argument('--options', metavar='FILE', help='Override 
advanced options via a json file.')parser.add_argument('--pallidum-separate', 
action='store_true', default=False, help='Move pallidum outside of global white 
matter class. Use this flag when T2/flair is used.')# optional lesion 
optionsparser.add_argument('--lesion', action='store_true', default=False, 
help='Enable lesion segmentation (requires 
tensorflow).')parser.add_argument('--threshold', type=float, default=0.3, 
help='Lesion threshold for final segmentation. Lesion segmentation must be 
enabled.')parser.add_argument('--samples', type=int, default=50, help='Number 
of samples for lesion segmentation. Lesion segmentation must be 
enabled.')parser.add_argument('--burnin', type=int, default=50, help='Number of 
burn-in samples for lesion segmentation. Les
 ion segmentation must be enabled.')parser.ad!
 d_argume
nt('--lesion-pseudo-samples', nargs=2, type=float, default=[500, 500], 
help='Lesion pseudo samples mean and 
variance.')parser.add_argument('--lesion-rho', type=float, default=50, 
help='Lesion ratio.')parser.add_argument('--lesion-mask-structure', 
default='Cortex', help='Intensity mask brain structure. Lesion segmentation 
must be enabled.')parser.add_argument('--lesion-mask-pattern', type=int, 
nargs='+', help='Lesion mask list (set value for each input volume): -1 below 
lesion mask structure mean, +1 above, 0 no mask. Lesion segmentation must be 
enabled.')# optional debugging optionsparser.add_argument('--history', 
action='store_true', default=False, help='Save 
history.')parser.add_argument('--save-posteriors', nargs='*', help='Save 
posterior volumes to the "posteriors" 
subdirectory.')parser.add_argument('--save-probabilities', action='store_true', 
help='Save final modal class probabilities to "probabilities" 
subdirectory.')parser.add_argument('--showfigs', action='store_true', defaul
 t=False, help='Show figures during run.')parser.add_argument('--save-mesh', 
action='store_true', help='Save the final mesh in template 
space.')parser.add_argum

[Freesurfer] R: SAMSEG "lesion" (Illegal instruction) ~ running VM_67

[Cerri, Stefano]

Hi Randy,

Yes, Tensorflow is installed in "freesurfer_7.2.0_amd64.deb". If it wasn't you 
would have obtained "no module named tensorflow" when running the command 
"import tensorflow".

Note that you are able to run "basic" SAMSEG since it does *not* require 
tensorflow. Only the lesion version (--lesion flag) requires that library.

I'm quite sure it is a problem with your CPU instruction set and the specific 
tensorflow version installed in FreeSurfer (v2.4.1). Unfortunately, I'm not 
able to help you further here. I hope someone else on the list can solve your 
issue.

Stefano

Da: daedalu...@aol.com 
Inviato: lunedì 28 febbraio 2022 14:52
A: Cerri, Stefano ; freesurfer@nmr.mgh.harvard.edu 

Oggetto: Re: [Freesurfer] SAMSEG "lesion" (Illegal instruction) ~ running VM_67


External Email - Use Caution

Hi Stefano and thanks for your response.

I have copied the output from my terminal window below, highlighting your 
instructed inputs.

When you say "SAMSEG requires Tensorflow", I am still trying to find out if 
Tensorflow was incorporated into "freesurfer_7.2.0_amd64.deb". (Installed 
2/8/2022)
If not, do I have to import and install it from somewhere else? (if so, then 
where/how?)

A colleague suggested I check where "tensor" might be found

developer@developer-VirtualBox:~$ env | grep -i tensor
(... returned nothing)

developer@developer-VirtualBox:~$ grep -i tensor $FREESURFER_HOME/bin/*
(... returned several instances of the term "tensor", but really only in 
"trac-preproc" / "orientLAS" / "dt_recon" / dmri_tensoreig" / "dmri_ac.sh")
(these make a certain amount of sense for the diffusion MRI routines)


As far as running this on another host, I am using the Virtual Machine as 
directed to from the Freesurfer Wiki:
VM_67 - Free Surfer Wiki 
(harvard.edu)<https://secure-web.cisco.com/193XQrgJe9FEWCJqsNZStMhYk4jsN7u7UndgFKbs78GBTEh6vcNYuo150WniP8eIrGI0GX-N8e0l4BiCM0wfnLjlYv1XWavKvXbIDaNYGiDvEVj8tIxEXwcymQcQ0sKuMBWZ-Da5-nD1G328WbM2kMm1W67MWjAZcYT1iC-SKyF0L3e7Vs68tCKjYv8XoLuvstPmjq43kZRRI9diTHGPAJ5qw73SiTJ9Zz9CrhDsSxSEABJmdU8VAs9XAlwwKMl5xH7tUy5cPFJQo9uueGOfA-dRhEobVgSA9-d_OROOYsVNbXkVEunpaBljfO5lah3Ex/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FVM_67>

I am running the VM on a Windows 10 Pro computer which is just a little over 2 
years old, and since the standard Freesurfer segmentation and the basic SAMSEG 
cross-sectional routines both work just fine, I don't know if the age of this 
system is truly the issue here.  This "illegal instruction (core dumped)" issue 
only happens when I try to use the --lesion flag.


x

Device secifications: (XXX's substituted for security reasons)

Device name DESKTOP-XX
Processor Intel(R) Core(TM) i7-9700K CPU @ 3.60GHz   3.60 GHz
Installed RAM 32.0 GB (31.8 GB usable)
Device ID CA89F214-3517-4D16-8A5D-XX
Product ID 00330-53014-11941-AAOEM
System type 64-bit operating system, x64-based processor


Windows specifications

Edition Windows 10 Pro
Version 21H2
Installed on ‎11/‎12/‎2020
OS build 19044.1526
Experience Windows Feature Experience Pack 120.2212.4170.0

x

Here is the output text-capture that I am seeing after I followed your 
instructions.  Yes, the error is replicated...


 freesurfer-linux-ubuntu18_x86_64-7.2.0-20210721-aa8f76b 
Setting up environment for FreeSurfer/FS-FAST (and FSL)
FREESURFER_HOME   /usr/local/freesurfer/7.2.0
FSFAST_HOME   /usr/local/freesurfer/7.2.0/fsfast
FSF_OUTPUT_FORMAT nii.gz
SUBJECTS_DIR  /usr/local/freesurfer/7.2.0/subjects
MNI_DIR   /usr/local/freesurfer/7.2.0/mni
developer@developer-VirtualBox:~$ fspython
Python 3.6.8 (default, Apr 10 2020, 02:08:58)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-23)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow
Illegal instruction (core dumped)
developer@developer-VirtualBox:~$


Thanks in advance for any further insights/directions.

-Randy

xxx

-Original Message-
From: Cerri, Stefano 
To: freesurfer@nmr.mgh.harvard.edu 
Cc: daedalu...@aol.com 
Sent: Sun, Feb 27, 2022 11:22 am
Subject: Re: [Freesurfer] SAMSEG "lesion" (Illegal instruction) ~ running VM_67

Hi Randy,

Your run_samseg syntax is correct and yes, the "lesion" version of SAMSEG 
requires Tensorflow.

The "illegal instruction" error is most probably related to an incompatible 
version of Tensorflow with your CPU instruction set. You should be able to 
replicate the error by typing:


  1.  fspython

  1.  import tensorflow

Would you be able to run SAMSEG lesion on another host mach

Re: [Freesurfer] SAMSEG Lesion images not written

[Cerri, Stefano]

Hi Randy,

"seg.mgz" is the "hard segmentation",  with lesion labeled as 99.

You have all the volumes in "samseg.stats".

If you want segmentation maps (values between 0 and 1), you should add the flag 
--save-posteriors to run_samseg. They will be saved in the samseg output 
directory under the "posteriors" folder.

You can get a lesion segmentation mask by binarizing the lesion probability map 
with mri_binarize.

Best,
Stefano

Dear experts

I was able to get SAMSEG --lesion to work on WSL (did not crash once I used 
float images instead of 16bit usign), but all that's being written out are 
listed below:


Folder: D:\0007_Subjects-FS\T1T2-lesion-float\
Files:
cost.txt
gaussians.rescaled.txt
mode01_bias_corrected.mgz
mode01_bias_field.mgz
mode01_scaling.txt
mode02_bias_corrected.mgz
mode02_bias_field.mgz
mode02_scaling.txt
samseg.stats
samseg.talairach.lta
sbtiv.stats
seg.mgz
template.lta
template_coregistered.mgz
template_transforms.mat
Since this is the first time got --lesion to run, I have no idea what the 
output "should" be.? Shouldn't some sort "lesion mask" be written out?
Thanks in advance for any insights/comments you might have
-Randy


XX
SNIPPET FROM THE END OF THE "SUCCESSFUL" SAMSEG --lesion run
XX

run_samseg -o $SUBJECTS_DIR/T1T2-lesion-float -i 
o_ADNI_002_S_4654__MRI-m072_float.nii 
rT1_o_ADNI_002_S_4654__MRI-m072_FLAIR_float.nii --pallidum-separate --lesion 
--lesion-mask-pattern 0 1 --threshold 0.7




Sample 44 times
Sample 45 times
Sample 46 times
Sample 47 times
Sample 48 times
Sample 49 times
Sample 50 times
thresholding posterior of? Lesions with threshold: 0.7
Constructing image-to-world transform from header information 
(o_ADNI_002_S_4654__MRI-m072_float.nii)
Read image: o_ADNI_002_S_4654__MRI-m072_float.nii
using default intracranial structures to compute sbtiv measure
run_samseg complete: 0:34:36.159030
daedalus@DESKTOP-TILLA3B:/usr/local/freesurfer/7-dev/subjects$



YAY!


XX
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Re: [Freesurfer] SAMSEG (Lesion Mask Pattern) ... ah, [0 0]

[Cerri, Stefano]

Hi Randy,

The default option is 0 for each input scan as no assumption on the MRI 
contrast and order of the input scans is made.  We strongly recommend users to 
use the value of 1 for both T2w and FLAIR scans and 0 for T1w scans.

The mask is reducing false-positive lesions by applying intensity constraints, 
but it also indirectly leads to better lesion segmentation overall as the model 
parameters are better estimated. So in general it's hard to disentangle its 
effect.

Hope it helps,
Stefano


From:
Subject: Re: [Freesurfer] SAMSEG (Lesion Mask Pattern) ... ah, [0 0]
To: "freesurfer@nmr.mgh.harvard.edu" 
Message-ID: <1991518757.1033.1648594478...@mail.yahoo.com>
Content-Type: text/plain; charset="utf-8"

External Email - Use Caution

Dear experts,?
I think have answered my own question, but it does raise one more.
>From the early lines in the reporting thread, I see that without 
>"--lesion-mask-pattern" flag, the default appears to be [0 0].??
New question:? From an accuracy/precision standpoint, what do you think the 
impact would be on lesion detection?
Thanks again (and in advance)
-Randy


-Original Message-
From: daedalu...@aol.com
To: freesurfer@nmr.mgh.harvard.edu 
Sent: Tue, Mar 29, 2022 4:24 pm
Subject: SAMSEG (Lesion Mask Pattern)

Dear experts,
I inadvertently omitted the lesion mask pattern [0 1] when running SAMSEG, and 
while it ran to completion, there were fewer voxels present in the lesion mask 
(both at thresh 0.3) when I re-ran SAMSEG using the LMP.? ?The SAMSEG run 
included a T1 and a co-registered T2-FLAIR image. I am curious as to what the 
software defaults to in the absence of the --lesion-mask-pattern information.
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[Freesurfer] Incorporating samseg segmentation into the recon-all pipeline

[Cerri, Stefano]

Hi Julian,

You can use the command "samseg" with the --recon flag. See the helper function 
for more details (--help)

Stefano

External Email - Use Caution

/Hello everyone,/



/We have been utilizing freesurfer for our brain morphometry and processing 
pipelines, and have recently tested the samseg segmentation algorithm on a 
clinical cohort./

/With respect to some regions, we currently prefer its results to the ones 
generated by the standard freesurfer segmentation algorithm.

/



/As SAMSEG only provides volume calculation (please correct me if I am wrong) 
and does not feature cortical thickness measurements,/

/I was wondering if the recon-all pipeline can be modified to utilize the 
samseg segmentation instead, and if so, which script(s) or chain of commands 
would be a good starting point to implement this./

/Looking forward to your feedback,/

/Julian
/

Julian McGinnis

PhD Candidate
TUM-Neuroimaging Center, School of Medicine, Technical University of Munich,
Munich, Germany
Department of Computer Science, Technical University of Munich, Munich, Germany

Email:julian.mcgin...@tum.de


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[Freesurfer] Large number of false negative MS lesions in SAMSEG

[Cerri, Stefano]

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 
Reply-To:   Freesurfer support list 

To: Freesurfer mailing list 




External Email - Use Caution

Hello,

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.png]
[image.png]

I would very much appreciate any leads as to how to improve the segmentation.

Thanks,

Martin
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[Freesurfer] R: Large number of false negative MS lesions in SAMSEG

[Cerri, Stefano]

Hi Martin,

Here are the instructions: 
https://surfer.nmr.mgh.harvard.edu/fswiki/FtpFileExchange

If you can, please upload both T1, T2, and FLAIR scans of that particular 
subject.

Thanks,
Stefano

Da: Martin Kavec 
Inviato: martedì 16 agosto 2022 03:42
A: Cerri, Stefano 
Cc: freesurfer@nmr.mgh.harvard.edu 
Oggetto: Re: [Freesurfer] Large number of false negative MS lesions in SAMSEG


External Email - Use Caution

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 
mailto:sce...@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 <mailto:martin.ka...@gmail.com>
Reply-To:   Freesurfer support list 
<mailto:freesurfer@nmr.mgh.harvard.edu>
To: Freesurfer mailing list 
<mailto:freesurfer@nmr.mgh.harvard.edu>



External Email - Use Caution

Hello,

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.png]
[image.png]

I would very much appreciate any leads as to how to improve the segmentation.

Thanks,

Martin

The information in this e-mail is intended only for the person to whom it is 
addressed.  If you believe this e-mail was sent to you in error and the e-mail 
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[Freesurfer] samseg lesions labels and values

[Cerri, Stefano]

Hi Dilek,

Yes, "--save-posteriors Lesions" will save a probability map with path 
*yourOutputDir*/posteriors/Lesions.mgz

1 and 2) Lesions are labeled as 99 in seg.mgz. A value of 0.04 in the stats 
file indicate that the lesion volume is 0.04 mm^3, so it makes sense that 
seg.mgz has no voxels labeled as 99.  However, it means that something went 
wrong with the segmentation. What was the command you used to segment these DIR 
images? I'd probably use --lesion-mask-pattern 1 for them (although I've never 
tried to run SAMSEG on DIR images). Do you have a T1w scan to add for better 
whole-brain segmentation and consequently better lesion segmentation?

3) You can use the lesion probability map obtained with the --save-posteriors 
Lesions flag and use mri_binarize and mri_segstats to obtain binary 
segmentation and corresponding volumes at different thresholds. Note that you 
don't need to use the same threshold of run_samseg.

Hope it helps,
Stefano

--

Message: 2
Date: Thu, 18 Aug 2022 19:45:14 +0300
From: Dilek ?zkan 
Subject: [Freesurfer] samseg lesions labels and values
To: freesurfer@nmr.mgh.harvard.edu
Message-ID:

Content-Type: text/plain; charset="utf-8"

External Email - Use Caution

Hello dear all,

I want to use Freesurfer-Samseg for MS lesion
segmentation(cross-sectional). I have read that I need to add
"--save-posteriors Lesions" to run_samseg to obtain lesion probabilities.

1)In the stats file I can see the value of "Lesions" (0.04) But when I try
to see on freeview, it says label=99 (lesion label) has no value. So, I
can't see the lesions.

2)There are a few labels related to lesions. For example wm lesions;
(498: wmsa, 499: other_wmsa) I have no volume related to these labels
neither in my stats file nor on freeview. Should I get only the "Lesions
label"  for the MS lesion mask?

3)As input, I am using only DIR ?mages. I w?ill try different thresholds. I
have read that by playing mri_binarize and mri_segstats, we can try
different thresholds without re-running anything. So, the threshold value
required for mri_binarize command refers to the same threshold input in the
initial the command of *run_samseg*?

Best,
Wish
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[Freesurfer] R: SAMSEG estimation error

[Cerri, Stefano]

Hi Giulio,

Although SAMSEG is a deterministic algorithm the default version might give you 
different results when executed with a different number of threads. These are 
small differences when looking at seg.mgz (a few voxels with swapped labels), 
but they are more visible when looking at volumes computed from soft 
segmentations like the stats files.

Note that you will obtain the same exact results when running SAMSEG with the 
same number of threads.

If you want to have cross-thread reproducible results with SAMSEG you can 
download the source files of FS 7.2 and build FS with the flag 
(GEMS_CROSS_THREAD_REPRODUCIBLE ON when doing cmake). Note that this version of 
SAMSEG will run slower than the original version.

Source files can be downloaded here: 
https://github.com/freesurfer/freesurfer/tags?after=v7.3.1

and instructions on how to build FS are here: 
https://surfer.nmr.mgh.harvard.edu/fswiki/BuildGuide

Hope it helps,
Stefano


Da: giulio siracusano 
Inviato: sabato 27 agosto 2022 04:22
A: freesurfer@nmr.mgh.harvard.edu 
Cc: Cerri, Stefano 
Oggetto: Re: [Freesurfer] SAMSEG estimation error


External Email - Use Caution

Hi Stefano,

I've investigated the use of SAMSEG for AD/MCI patients. I'm using the 7.2 
version of Freesurfer and I've realized that I get different results using the 
same data but when I run the SAMSEG multiple times.

Differently from using ASEG, SAMSEG provides also the chance to execute the 
code using multiple threads.

In the first run I've executed SAMSEG on ADNI patient id 002_S_0685 using the 
MP-RAGE series having ID I18211 (the link below provides the NIFTI version of 
the series which has been used for the processing).

https://drive.google.com/drive/folders/15oghna17Qz-OSuo9E3-rldOt935AEEuO?usp=sharing<https://secure-web.cisco.com/1kjcQ6V-ZSEdfK2uygax7NBB93ggYjLmfqbPpwSpeHhQevXMkepVFRYeckjpgVHV1Oh-uMLgjGFKI2PfVRNiGQTK5Dy4PIAShzp5i5bimEXKxeKoS713q15oMAwcQhSKATzEmPHGzN8asmgshA5ht7lmRmBLOjQ3Xym0hFW2JhMPHCuQwvRnE6QRghkwv-ESvMN0G3rFtnEvS5kCBMxXH9ucX5ChFJLkS9Q0fI5AKpZQ_LD0_QMiVFn5qsKGbb9aLlcFY9Qrd7s7tAZbnw_5hrpktiA4_6pudckEKwVW97JppQE6e78a0Z0Ay4m-uGLOx/https%3A%2F%2Fdrive.google.com%2Fdrive%2Ffolders%2F15oghna17Qz-OSuo9E3-rldOt935AEEuO%3Fusp%3Dsharing>

The first execution of SAMSEG was with default settings (1 thread) and results 
are attached, the second was using --threads 6.

These results from the SAME series are similar but they are NOT the same.

How can we explain that?

Regards

Giulio
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[Freesurfer] R: SAMSEG estimation error

[Cerri, Stefano]

Hi Giulio,

This is odd. I've run your scan on my computer two times using both a single 
thread and 8 threads with the default FS 7.2 and obtained the same results 
within the same number of threads.

Regarding the np.random functions, these are called only by the lesion version 
-- which, by the way, we have fixed in version 7.3 the seed to obtain 
reproducible results.

Are you sure you're running these commands on the same machine?

Stefano


Da: giulio siracusano 
Inviato: sabato 27 agosto 2022 14:15
A: Cerri, Stefano 
Cc: giulio siracusano ; 
freesurfer@nmr.mgh.harvard.edu 
Oggetto: Re: [Freesurfer] SAMSEG estimation error


External Email - Use Caution

Hi Stefano,
thanks a lot for the reply.
Unfortunately, I've realized that even when you run the same command with a 
single-thread (see attached results 1 and 3) you get slighly different results,
which are also different against the multi-thread execution (result 2).
I've checked the code in Python for samseg (in 
/usr/local/freesurfer/7.2.0/python/packages/samseg) and I can see there are 
several calls to np.random,
without setting the pseudonumber generator (such as with np.random(1234)).
This of course might have implications on the reproducibility of the results, 
although I think most of the code is in a compiled library.
You can check yourself using the file I've shared with you on google drive.
I agree with you that, based on the implementation, running SAMSEG with a 
multi-thread execution (i.e. using --threads flag) causes a non-deterministic 
behaviour and the results will not be reproducible.
Of course, we are talking about very very small variations (<0.1%) among 
results, but it is something disappointing (at least when using default 
settings which imply a single-thread execution).
Thanks for letting me know about this option when compiling the source code.

Regards

Giulio

On Sat, 27 Aug 2022 at 17:38, Cerri, Stefano 
mailto:sce...@mgh.harvard.edu>> wrote:
Hi Giulio,

Although SAMSEG is a deterministic algorithm the default version might give you 
different results when executed with a different number of threads. These are 
small differences when looking at seg.mgz (a few voxels with swapped labels), 
but they are more visible when looking at volumes computed from soft 
segmentations like the stats files.

Note that you will obtain the same exact results when running SAMSEG with the 
same number of threads.

If you want to have cross-thread reproducible results with SAMSEG you can 
download the source files of FS 7.2 and build FS with the flag 
(GEMS_CROSS_THREAD_REPRODUCIBLE ON when doing cmake). Note that this version of 
SAMSEG will run slower than the original version.

Source files can be downloaded here: 
https://github.com/freesurfer/freesurfer/tags?after=v7.3.1<https://secure-web.cisco.com/1f6_OrrMtkirHO7dyqPm2qDT9b28pekhPVqQDcrIico18JMZJFze8NUMfEmUyZL_ET3c5k6hPg_ul_SYvt8iHOnbZGCiik3UoA9NCuBbQWCQ5eeJiNr7EcPuCHlQKNIoctCSq_92TxkdVOjBg2kGAnVK_1gEyHrJ_dAQ6rkNvKJac1gAZcq9xLpq42f2h2DP0yhhiE-pWBcUkQ-inW1ONYfFXcIs_PWVI4Am1yxVbV5O_cOh3b5XTaonmrlzgV52sWROlqI1brHtmhIEK5Y_KVdZp9Cf9YiN6jbG5o-8l4mFiySHc8unvHScbT5g6Kmjr/https%3A%2F%2Fgithub.com%2Ffreesurfer%2Ffreesurfer%2Ftags%3Fafter%3Dv7.3.1>

and instructions on how to build FS are here: 
https://surfer.nmr.mgh.harvard.edu/fswiki/BuildGuide<https://secure-web.cisco.com/1CaXd2_aFCyTRvuzpyKfKWpi8AQAZcUmyziYiFtuz41i6XVpkRWrd_FAre0ODDRkOUV5uzxaxka461mo5ZANOTULK21YPIagBLfcPWuRiWCTk-31wWC1V7PA8l_UT7TWEAaaeKX5QyiWMmqBEjXo923vWrxgAetrsjJ-ckAcy9_Vz98qo5j3-Ecf4lQlGjTCy7pL7adLkSE-65OwzZJx0QUu74gGhZsm_giG9eYGitfDU8vXaLKzWgdPCRuxJ-Xvpegne6rGL1L9uvNBuG3JD1Q7nLwvAMuJJ_vfz4N-Ea9rLnSVAQUvosNavo-YeUJ3d/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FBuildGuide>

Hope it helps,
Stefano


Da: giulio siracusano 
mailto:siracusanogiu...@gmail.com>>
Inviato: sabato 27 agosto 2022 04:22
A: freesurfer@nmr.mgh.harvard.edu<mailto:freesurfer@nmr.mgh.harvard.edu> 
mailto:freesurfer@nmr.mgh.harvard.edu>>
Cc: Cerri, Stefano mailto:sce...@mgh.harvard.edu>>
Oggetto: Re: [Freesurfer] SAMSEG estimation error


External Email - Use Caution

Hi Stefano,

I've investigated the use of SAMSEG for AD/MCI patients. I'm using the 7.2 
version of Freesurfer and I've realized that I get different results using the 
same data but when I run the SAMSEG multiple times.

Differently from using ASEG, SAMSEG provides also the chance to execute the 
code using multiple threads.

In the first run I've executed SAMSEG on ADNI patient id 002_S_0685 using the 
MP-RAGE series having ID I18211 (the link below provides the NIFTI version of 
the series which has been used for the processing).

https://drive.google.com/drive/folders/15oghna17Qz-OSuo9E3-rldOt935AEEuO?usp=sharing<htt

Re: [Freesurfer] samseg inputs

[Cerri, Stefano]

Hi Dilek,

I've actually run SAMSEG-lesion on some gadolinium-enhanced scans in the paper. 
Look at the top row of Fig. 7 ("T1c") and at the "MSseg" dataset. I did not 
check the performance of the method on such data. We also don't distinguish 
between enhanced and non-enhanced lesions.

I would probably set --lesion-mask-pattern to "0" if you want to segment most 
of the lesions, or --lesion-mask-pattern to "1" if you want to segment only the 
enhanced lesions.

It is usually not advised to analyze segmentations/volumes obtained using 
different contrasts as you might introduce biases in your analysis.

Let us know how it goes,
Stefano



Hello dear all,

I want to use Freesurfer-Samseg for MS lesion
segmentation(cross-sectional). I have read the paper, accordingly I want to
try the t1-flair combination in terms of the accuracy.

Do you have any experience with T1 images with contrast agent? I couldn't
find anything related to those in the paper. Can I use t1 with contrast in
a few patients if the patient doesn't have t1 image without contrast agent?
i will declare this situation in the results.

Best,
Dilek

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Re: [Freesurfer] Samseg dice is low

[Cerri, Stefano]

Hi Dilek,

0.2 Dice seems extremely low. Also, in my experience, a threshold of 0.05 on 
T1w-FLAIR scans will show up many FP lesions.

We usually reported a Dice in the range of 0.50-0.65 on various datasets (MS 
and WMH, default threshold, T1w-FLAIR), so I'm surprised by a such low value.

Can you share with us your run_samseg command?

Stefano

Date: Sun, 4 Sep 2022 15:53:17 +0300
From: Dilek ?zkan 
Subject:    
To: Freesurfer support list 
Message-ID:

Content-Type: text/plain; charset="utf-8"

External Email - Use Caution

Hello all,

I use Freesurfer-Samseg for MS lesion segmentation(cross-sectional).

I use the T1 and Flair for this. (just these are inputs) I registered *flair
and t1 to DIR *for every patient. (My manual lesion masks are on DIR
imaging.) I controlled the registrations, these are true.

I created a binary lesion mask using *threshold 0.05. *(mri_binarize --i
/data/projects/MS_MRI/posteriors/Lesions.mgz --o
/data/projects/MS_MR/binarize/lesion_binary.mgz --min 0.05)
I checked the dice score with ground truth values with python.

*threshold *0.05= *dice* 0,2 of the dataset

Do you have any recommendations to increase the dice?

# cvs_version 7.2.0
# sysname Linux
# machine x86_64

Best regards
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Re: [Freesurfer] samseg longitudinal processing - process killed

[Cerri, Stefano]

Hi yvg,


It is most likely a memory error problem. You will need to allocate more RAM to 
your calls. You probably need at least 32GB or RAM for such big images (might 
be even more).


You can process the FLAIR images with mri_robust_template since they are 
slighly smaller than your T1 images.


Stefano



Dear Samseg developers,

I have very high resolution T1 (512 x 512 x 240; voxel size: 0.469 x 0.469
x 1) and FLAIR images ( 384 x 384 x 128; voxel size: 0.495 x 0.495 x 1) and
I would like to process them with the longitudinal processing of samseg but
I have encountered different issues:

1.- mri_robust_template with T1 images: the process is killed after the
following steps:

 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 )

./samseg_mutua.sh: line 20: 1511261 Killed
 mri_robust_template ...

2.- mri_robust_template with FLAIR images can be processed without errors,
but when I execute run_samseg_long to the FLAIR images, the process is
killed without further explanations after the following command:

"Transforming points[0.49479165 0.49479164 0.49479165]".

Could you please please help me?

Best,
yvg

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[Freesurfer] R: SAMSEG Lesion images not written

[Cerri, Stefano]

Hi Giulio,

I'm not sure I understand what your goal is. Are you just trying to visualize 
specific brain structures over your input image? Are you interested in 
segmentation maps or binary segmentations?

If you want to visualize segmentation maps, you can just use Freeview and load 
the specific structure file(s). Note that these segmentation maps are 1) not 
binary, i.e., they have values *between* 0 and 1, and 2) they are in the same 
space as your input image.

If you want to visualize binary segmentation for specific structures you can do 
this in Freeview. You load your segmentation (seg.mgz) as a lookup table and 
select only the label values that you're interested in.

Hope it helps,
Stefano

Da: Giulio Siracusano 
Inviato: domenica 27 novembre 2022 04:01
A: Cerri, Stefano ; freesurfer@nmr.mgh.harvard.edu 

Oggetto: Re: [Freesurfer] SAMSEG Lesion images not written


External Email - Use Caution

Hi Stefano,
I'd like to ask you a question wrt SAMSEG.
I'd like to extract segmentation maps using SAMSEG, and I know already that we 
have to use '--save-posteriors' option when running the command.

They will be saved in the samseg output directory under the "posteriors" folder.

How is it possible, starting from these binary segmentation maps, creating 
multiple images of the brain where a given (segmentated) region is highlighed?
In order to do that, you have to multiply a given reference brain images -over- 
each segmentation map (which is a binary matrix with 0's and 1's).
What is the reference brain image all these segmentation maps are related to?

I hope to be clear enough

Best regards
Giulio Siracusano
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[Freesurfer] R: SAMSEG Lesion images not written

[Cerri, Stefano]

Great!

You can use the command "samseg" with the flag "--recon" instead of 
"run_samseg". This will first run SAMSEG to obtain a whole-brain segmentation, 
then recon-all will use this segmentation to perform surface analysis and 
cortical parcellation -- instead of using ASEG segmentation. Look at the help 
function for more information.

Stefano

Da: Giulio Siracusano 
Inviato: domenica 27 novembre 2022 10:07
A: Cerri, Stefano 
Cc: freesurfer@nmr.mgh.harvard.edu 
Oggetto: Re: [Freesurfer] SAMSEG Lesion images not written


External Email - Use Caution

Hi Stefano,
I've got this thanks. I simply use freeview and ingest region-specific .mgz 
files.

I just wanted to understand one thing.
I realize that using SAMSEG or ASEG it is possible to obtain subcortical 
segmentation (44 parameters are visualized, representing different regions).
I realized that fusiform gyrus, middle temporal and entorhinal cortex volumes 
cannot be derived using one of the above mentioned methods.
I just wanted to know if is there any way to achieve cortical parcellation 
without using ASEG?
Or, in alternative, is there a way to estimate fusiform gyrus, middle temporal 
and entorhinal cortex volumes from the variables obtained in samseg.stats?

Hope to be clear

Giulio Siracusano






On Sun, 27 Nov 2022 at 14:22, Cerri, Stefano 
mailto:sce...@mgh.harvard.edu>> wrote:
Hi Giulio,

I'm not sure I understand what your goal is. Are you just trying to visualize 
specific brain structures over your input image? Are you interested in 
segmentation maps or binary segmentations?

If you want to visualize segmentation maps, you can just use Freeview and load 
the specific structure file(s). Note that these segmentation maps are 1) not 
binary, i.e., they have values *between* 0 and 1, and 2) they are in the same 
space as your input image.

If you want to visualize binary segmentation for specific structures you can do 
this in Freeview. You load your segmentation (seg.mgz) as a lookup table and 
select only the label values that you're interested in.

Hope it helps,
Stefano

Da: Giulio Siracusano 
mailto:giuliosiracus...@gmail.com>>
Inviato: domenica 27 novembre 2022 04:01
A: Cerri, Stefano mailto:sce...@mgh.harvard.edu>>; 
freesurfer@nmr.mgh.harvard.edu<mailto:freesurfer@nmr.mgh.harvard.edu> 
mailto:freesurfer@nmr.mgh.harvard.edu>>
Oggetto: Re: [Freesurfer] SAMSEG Lesion images not written


External Email - Use Caution

Hi Stefano,
I'd like to ask you a question wrt SAMSEG.
I'd like to extract segmentation maps using SAMSEG, and I know already that we 
have to use '--save-posteriors' option when running the command.

They will be saved in the samseg output directory under the "posteriors" folder.

How is it possible, starting from these binary segmentation maps, creating 
multiple images of the brain where a given (segmentated) region is highlighed?
In order to do that, you have to multiply a given reference brain images -over- 
each segmentation map (which is a binary matrix with 0's and 1's).
What is the reference brain image all these segmentation maps are related to?

I hope to be clear enough

Best regards
Giulio Siracusano

The information in this e-mail is intended only for the person to whom it is 
addressed.  If you believe this e-mail was sent to you in error and the e-mail 
contains patient information, please contact the Mass General Brigham 
Compliance HelpLine at 
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[Freesurfer] [FreeSurfer] ValueError axes don't match array

[Cerri, Stefano,PHD]

External Email - Use Caution

Hi Krystal,

Can you send your samseg command and the output of mri_info on both the T1 and 
coregistered FLAIR images? It seems that the two images have different image 
sizes.

Stefano

Subject:[Freesurfer] [FreeSurfer] ValueError axes don't match array
Date:   Tue, 22 Aug 2023 04:22:09 +
From:   Krystal Xiwing Yau 
Reply-To:   Freesurfer support list 

To: freesurfer@nmr.mgh.harvard.edu 




External Email - Use Caution

Dear FreeSurfer experts,


I have completed the processes of coregistration of FLAIR to T1 image for the 
subject. As I ran samseg with lesion contrast, the following error message 
occurred:


writing template transform to 
/home/admin1/freesurfer/subjects/103_samsegOutput/template.lta
writing talairach transform to 
/home/admin1/freesurfer/subjects/103_samsegOutput/samseg.talairach.lta
atlas registration complete: 0:00:17.614971
/home/admin1/freesurfer/python/lib/python3.8/site-packages/numpy/core/_asarray.py:83:
 VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences 
(which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths 
or shapes) is deprecated. If you meant to do this, you must specify 
'dtype=object' when creating the ndarray
  return array(a, dtype, copy=False, order=order)
Traceback (most recent call last):
  File "/home/admin1/freesurfer/python/scripts/run_samseg", line 190, in 

_, _, _, optimizationSummary = samseg.segment(
  File "/home/admin1/freesurfer/python/packages/freesurfer/samseg/Samseg.py", 
line 255, in segment
self.preProcess()
  File "/home/admin1/freesurfer/python/packages/freesurfer/samseg/Samseg.py", 
line 318, in preProcess
self.imageBuffers, self.transform, self.voxelSpacing, self.cropping = 
readCroppedImages(
  File 
"/home/admin1/freesurfer/python/packages/freesurfer/samseg/SamsegUtility.py", 
line 139, in readCroppedImages
croppedImageBuffers = np.transpose(croppedImageBuffers, axes=[1, 2, 3, 0])
  File "<__array_function__ internals>", line 5, in transpose
  File 
"/home/admin1/freesurfer/python/lib/python3.8/site-packages/numpy/core/fromnumeric.py",
 line 653, in transpose
return _wrapfunc(a, 'transpose', axes)
  File 
"/home/admin1/freesurfer/python/lib/python3.8/site-packages/numpy/core/fromnumeric.py",
 line 55, in _wrapfunc
return _wrapit(obj, method, *args, **kwds)
  File 
"/home/admin1/freesurfer/python/lib/python3.8/site-packages/numpy/core/fromnumeric.py",
 line 44, in _wrapit
result = getattr(asarray(obj), method)(*args, **kwds)
ValueError: axes don't match array

Would somebody be kindly advise? Thank you.

Regards,
Krystal

Tel.: +852 2255 5024
Fax: +852 2872 5828
Address: Room 304, 3/F, New Clinical Building, 102 Pokfulam Road, Hong Kong.

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Re: [Freesurfer] Samseg cortex parcellation

[Cerri, Stefano,PHD]

Hi Valentin,

Glad to hear that.

Did you use the command "samseg" with the --recon flag? If yes, there are a 
couple of flags that you can add so that the output of SAMSEG ("seg.mgz") is 
used in more steps in the recon-all stream:

"  --fill : use samseg to create filled.mgz instead of recon-all"
"  --normalization2 : use samseg to create brain.mgz instead of recon-all (with 
--recon) "

Would you be able to run the command with these flags (--fill and 
--normalization2) and let us know if you obtain better surfaces and hence 
cortical parcellations?

Thanks,
Stefano

Date: Thu, 16 Feb 2023 23:32:49 +
From: "Stepanov, Valentin" 
Subject: [Freesurfer] Samseg cortex parcellation
To: "freesurfer@nmr.mgh.harvard.edu" 
Message-ID: <7d31c671-938e-456e-a533-8a132b6e6...@nyulangone.org>
Content-Type: text/plain; charset="utf-8"

External Email - Use Caution

Hello, I hope this email finds you well.

I am using Samseg for the MS patients' data and am very impressed with its 
performance in terms of lesions segmentation along with posteriors and 
probability maps saving. Also, compared to freesurfer, it has a remarkably 
better quality of cortical gray matter segmentation, particularly in subjects 
with juxta/intracortical lesions. However, to my knowledge, it does not allow 
doing a cortex parcellation. I used it with the ?recon option, but in that 
case, the output (aparc+aseg.mgz) is identical or very close to those 
freesurfer provides and commonly has some segmentation errors, whereas seg.mgz 
saved in samseg directory demonstrates significantly better segmentation.
I wonder if there is any way to run cortex parcellation using exact samseg 
seg.mgz output?
I have attached a couple of images demonstrating the difference of segmentation 
output for freesurfer and samseg.

Thank you,

Best regards
Valentin

Valentin Stepanov
Postdoctoral Fellow
Center for Biomedical imaging
Department of Radiology
NYU Grossman School of Medicine
660 1st Avenue, office 212
New York, NY 10016

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Re: [Freesurfer] SAMSEG in MS terminal error

[Cerri, Stefano,PHD]

Hi Gabriel,

These messages look like TensorFlow warnings. They just mean that you're 
running it on a system without GPUs. They should not stop the run.

Is this the last message printed by run_samseg, or does the algorithm 
continues? Can you provide more details on when the run terminates?

Stefano

External Email - Use Caution

Hi, I'm having difficulty with the command to assess WM lesion in MS, using
the SAMSEG.

I have already installed tensorflow and python3.9, however when typing in
the terminal the command "run_samseg --input /home/username/data/t1.nii
/home/username/data/flair.nii --pallidum-separate --lesion
--lesion-mask-pattern 0 1 --output /home/username/data/samsegOutput", this
message appears:

"2023-03-24 13:21:04.936769: W
tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not
load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0:
cannot open shared object file: No such file or directory
2023-03-24 13:21:04.936787: I
tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart
dlerror if you do not have a GPU set up on your machine.
WARNING:tensorflow:From
/usr/local/freesurfer/7.2.0/python/lib/python3.6/site-packages/tensorflow/python/compat/v2_compat.py:96:
disable_resource_variables (from tensorflow.python.ops.variable_scope) is
deprecated and will be removed in a future version.
Instructions for updating:
non-resource variables are not supported in the long term"


--
Att,

Gabriel de Deus Vieira
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Re: [Freesurfer] Samseg lesion mask holes

[Cerri, Stefano,PHD]

Hi Evie,

--save-probabilities and --save-posteriors will save two different things for 
lesions. The former is an initialization of lesions based on intensity and 
location constraints, and the latter is a probability map of seg.mgz after we 
also introduce lesion shape constraints (Cf Fig.4 of 
https://www.sciencedirect.com/science/article/pii/S1053811920309563).

The output of --save-probabilities should give you a very noisy lesion 
probability map with lots of false positives (at least this is my experience). 
In your case, it seems that too many *true* lesions are removed when the shape 
model is introduced. Would you be able to provide the command you're using to 
segment your T2-FLAIR scans? Which --lesion-mask-pattern values are you using 
for this input combination?

Stefano

Evie Neylon Tue, 28 Mar 2023 07:15:17 -0700

External Email - Use Caution

Dear experts,

I am running SAMSEG to segment MS lesions from T2 FLAIR scans. I wanted to
create a lesion mask in order to obtain lesion volumes and lesion counts,
so I used mri_binarize on seg.mgz to obtain all voxels with the value 99.
However, upon visualising this mask I see that there are holes in the mask
in regions that are quite clearly lesions based on the FLAIR image. I see
in seg.mgz that these voxels are instead assigned incorrectly to a
different tissue, as the lateral ventricle, for example.

I wondered if this misassignation of tissue was due to the chosen threshold
(0.3) so I added the --save-probabilties flag to look at the
probability maps too, and I see that actually the probability map
thresholded at 0.3 does not contain holes. The probability map actually
seems more accurate in general and picks up on more of the
hyperintensities. This is important for my desired outputs (i.e. accurate
lesion counts/volumes).

So I wondered if it was possible to explain a little why these holes might
be occurring in the final segmentation but not the probability map?
Would it be incorrect to derive the lesion mask from the probability map
instead?

Apologies I cannot attach the images of the data.

TIA,
Evie
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[Freesurfer] R: Samseg lesion mask holes

[Cerri, Stefano,PHD]

Hi Evie,

The commands look good to me. It's hard to say what is happening without 
looking at the images.

One possible way to decrease false negative lesions is to relax the intensity 
masking of the lesions. Either by setting --lesion-mask-pattern to 0 or by 
masking voxels based on the mean of the WM class (default is GM), e.g.:

--lesion-mask-structure White --lesion-mask-pattern 1

However, these changes might increase false positive lesions.

Stefano

Da: Evie Neylon 
Inviato: venerdì 31 marzo 2023 04:28
A: Cerri, Stefano,PHD 
Cc: freesurfer@nmr.mgh.harvard.edu 
Oggetto: Re: [Freesurfer] Samseg lesion mask holes


External Email - Use Caution

Hi Stefano,

Thank you for your reply and explanation.

The command I'm using to segment FLAIR is as follows:

run_samseg --input T2_FLAIR.nii.gz  --output samseg_outputs --threads 8 
--lesion --lesion-mask-pattern 1 --threshold 0.3 --save-posteriors 
--save-probabilities

In some cases we're also including T1 gadolinium scans together with the FLAIR 
(co-registered) and use the following:

run_samseg --input T2_FLAIR.nii.gz T1_gad.nii.gz --output samseg_outputs 
--threads 8 --lesion --lesion-mask-pattern 1 1 --threshold 0.3 
--save-posteriors --save-probabilities


Thanks again for your help,
Evie

On Wed, Mar 29, 2023 at 2:08 PM Cerri, Stefano,PHD 
mailto:sce...@mgh.harvard.edu>> wrote:
Hi Evie,

--save-probabilities and --save-posteriors will save two different things for 
lesions. The former is an initialization of lesions based on intensity and 
location constraints, and the latter is a probability map of seg.mgz after we 
also introduce lesion shape constraints (Cf Fig.4 of 
https://www.sciencedirect.com/science/article/pii/S1053811920309563<https://secure-web.cisco.com/1mrQDWBGyHmcqV-0zPdZJ2rNhvKxIzCJhhoSrRk3g6xcnhHCLbgWMpaL0fkesG4MrEs5lRRo3jD2NgdHQBN0dGk4AJ0RxCdjwbhNLHBq40sgy2MeUWc8SR0zQcYunVVZeLpmHu2xg1J2rkpIVuZe4m6tMc55sS5zHiEE6YMYz5eei2-CY9oMrlTxxEx6ZB67XIW3mfDSpFCV1E9Mxz5MiExw8gWZE1W4XrnEyrbT6B9cZRxvcGTkUdGGXW_GA_YTnGr57Zsc3XJovAOV5ZMEdoczZNai6_zmnpzGR3jvUeKhhFOQI8SqkJIp6_En5xL18/https%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS1053811920309563>).

The output of --save-probabilities should give you a very noisy lesion 
probability map with lots of false positives (at least this is my experience). 
In your case, it seems that too many *true* lesions are removed when the shape 
model is introduced. Would you be able to provide the command you're using to 
segment your T2-FLAIR scans? Which --lesion-mask-pattern values are you using 
for this input combination?

Stefano

Evie Neylon Tue, 28 Mar 2023 07:15:17 -0700

External Email - Use Caution

Dear experts,

I am running SAMSEG to segment MS lesions from T2 FLAIR scans. I wanted to
create a lesion mask in order to obtain lesion volumes and lesion counts,
so I used mri_binarize on seg.mgz to obtain all voxels with the value 99.
However, upon visualising this mask I see that there are holes in the mask
in regions that are quite clearly lesions based on the FLAIR image. I see
in seg.mgz that these voxels are instead assigned incorrectly to a
different tissue, as the lateral ventricle, for example.

I wondered if this misassignation of tissue was due to the chosen threshold
(0.3) so I added the --save-probabilties flag to look at the
probability maps too, and I see that actually the probability map
thresholded at 0.3 does not contain holes. The probability map actually
seems more accurate in general and picks up on more of the
hyperintensities. This is important for my desired outputs (i.e. accurate
lesion counts/volumes).

So I wondered if it was possible to explain a little why these holes might
be occurring in the final segmentation but not the probability map?
Would it be incorrect to derive the lesion mask from the probability map
instead?

Apologies I cannot attach the images of the data.

TIA,
Evie
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Re: [Freesurfer] Longitudinal SAMSEG with multi-contrast data

[Cerri, Stefano,PHD]

External Email - Use Caution

Hi Gonzalo,

Assuming that you have run mri_robust_template and obtained longitudinally 
registered images (e.g., tp0_t1_reg.mgz, tp1_t1_reg.mgz, etc...), then you can 
co-register each additional contrast of each time point with the commands:

mri_coreg --mov tp0_flair.nii --ref tp0_t1_reg.mgz --reg tp0_FLAIRtoT1.lta
mri_vol2vol --mov tp0_flair.nii --reg tp0_FLAIRtoT1.lta --o tp0_flair_reg.mgz 
--targ tp0_t1_reg.mgz

for time-point 0 and

mri_coreg --mov tp1_flair.nii --ref tp1_t1_reg.mgz --reg tp1_FLAIRtoT1.lta
mri_vol2vol --mov tp1_flair.nii --reg tp1_FLAIRtoT1.lta --o tp1_flair_reg.mgz 
--targ tp1_t1_reg.mgz

for time-point 1, etcetera.

Stefano

[Freesurfer] Longitudinal SAMSEG with multi-contrast 
data

Gonzalo Rojas 
Costa
 Mon, 12 Jun 2023 10:21:51 
-0700

External Email - Use Caution

Hi:

  How can I generate "tp1_flair_reg.mgz" image appeared in command
"run_samseg_long --timepoint tp0_t1_reg.mgz tp0_flair_reg.mgz --timepoint
tp1_t1_reg.mgz tp1_flair_reg.mgz --timepoint tp2_t1_reg.mgz
tp2_flair_reg.mgz --output outputDir/" ?

  Sincerely,


Gonzalo Rojas Costa


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