Re: [Freesurfer] Hippocampal Subfields Posterior Probability

[Bharadwaj, Pradyumna - (prad)]

Great! Thank you for taking that time to clarify that.


-Prad


From: freesurfer-boun...@nmr.mgh.harvard.edu 
 on behalf of Iglesias Gonzalez, 
Eugenio 
Sent: Wednesday, March 22, 2017 11:34 AM
To: Freesurfer support list
Subject: Re: [Freesurfer] Hippocampal Subfields Posterior Probability

Hi again, Prad,
In that case, you don’t need the discrete segmentations. Just look at the 
posteriors directly.
Cheers,
/Eugenio


Juan Eugenio Iglesias
ERC Senior Research Fellow
Translational Imaging Group
University College London
http://www.jeiglesias.com
http://cmictig.cs.ucl.ac.uk/


On 22 Mar 2017, at 18:26, Bharadwaj, Pradyumna - (prad) 
mailto:p...@email.arizona.edu>> wrote:

Sorry about that. I should have stated what I was trying to do. I'm trying to 
see if the posterior probability changes when using a certain combination of 
the different T1 and T2 weighted scans that we have in our lab. I thought using 
the binary masks to extract the probabilities as they were the final volumes of 
the subfields would be a better way.


As an example,
when I extract some basic stats on the left CA1 posteriors for one subject, 
these are the values I get,
range: 0.15 to 1, with a mean (sd) of 0.245258 (0.335046);

and , when I use the binary mask of the CA1 from lh.hippoSfLabels-T1.v10.mgz 
and then extract the same basic stats, I get,

range: 0.247501 to 1, with a mean (sd) of 0.770796 (0.175752)

Is my approach incorrect ?

Thanks!,
-Prad



From: 
freesurfer-boun...@nmr.mgh.harvard.edu<mailto:freesurfer-boun...@nmr.mgh.harvard.edu>
 
mailto:freesurfer-boun...@nmr.mgh.harvard.edu>>
 on behalf of Iglesias Gonzalez, Eugenio 
mailto:e.igles...@ucl.ac.uk>>
Sent: Wednesday, March 22, 2017 11:06 AM
To: Freesurfer support list
Subject: Re: [Freesurfer] Hippocampal Subfields Posterior Probability

Hi Prad,
The final probabilities are in the posterior files. There’s no need to binarize 
?h.hippoSfLabels if what you’re interested in is the soft segmentations.
Or maybe I’m missing something? What are you exactly trying to do?
Cheers,
/E

Juan Eugenio Iglesias
ERC Senior Research Fellow
Translational Imaging Group
University College London
http://www.jeiglesias.com<http://www.jeiglesias.com/>
http://cmictig.cs.ucl.ac.uk/


On 22 Mar 2017, at 18:02, Bharadwaj, Pradyumna - (prad) 
mailto:p...@email.arizona.edu>> wrote:

Hi Dr. Iglesias,

Thank you for the overview of the labeling rules. I have also tried setting 
WRITE_POSTERIORS to 1 to write out the posteriors.

I had a follow up question about obtaining the probabilities for the final 
subfield labels as available in the ?h.hippoSfLabels-T1.v10.mgz

I use mri_binarize on ?h.hippoSfLabels-T1.v10.mgz to obtain binary masks for 
each subfield, and then used these masks with their respective posteriors to 
obtain the distributions.

Is this procedure correct or is there a better way ?

Thanks,
-Prad

From: 
freesurfer-boun...@nmr.mgh.harvard.edu<mailto:freesurfer-boun...@nmr.mgh.harvard.edu>
 
mailto:freesurfer-boun...@nmr.mgh.harvard.edu>>
 on behalf of Iglesias Gonzalez, Eugenio 
mailto:e.igles...@ucl.ac.uk>>
Sent: Tuesday, March 21, 2017 2:22 PM
To: Freesurfer support list
Subject: Re: [Freesurfer] Hippocampal Subfields Posterior Probability

Dear Prad,
There is a “secret” way of getting the posteriors. You need to set the 
environment variable WRITE_POSTERIORS to 1 before you call recon-all.
In (t)csh:
setenv WRITE_POSTERIORS 1
In bash:
export WRITE_POSTERIORS=1
And then call recon-all -hippocampal-subfields-T1(T2) as usual.

The discrete segmentation picks, for each voxel, the most likely label. The 
posterior of this label might or might not be above 0.5. For instance, if a 
voxel has p=0.4 of being CA1, p=0.3 of being background, and p=0.3 of being 
fimbria, it will be labeled as CA1 (even though p<0.5 for such subfield). Some 
people seem to prefer a 2-stage approach, in which a hippocampal mask is first 
created by selecting the voxels for which p(background)<0.5, and then each 
voxel within that mask is colored with the most likely subfield at that 
location.

I hope this helps!

Cheers,

/Eugenio



Juan Eugenio Iglesias
ERC Senior Research Fellow
Translational Imaging Group
University College London
http://www.jeiglesias.com<http://www.jeiglesias.com/>
http://cmictig.cs.ucl.ac.uk/


On 21 Mar 2017, at 20:09, Bharadwaj, Pradyumna - (prad) 
mailto:p...@email.arizona.edu>> wrote:

Hello Dr. Iglesias,

I'm currently examining the distributions of the posterior probabilities of the 
different hippocampal subfields, and I'm interested in obtaining the 
probability distribution images for the subfields that correspond to the 
volumes output in the subjects text file.

While I can use mri_binarize on ?h.hippoSfLabels-T1.v10.mgz to obtain the 
subfield masks and use them to obtain the posterior 

Re: [Freesurfer] Hippocampal Subfields Posterior Probability

[Iglesias Gonzalez, Eugenio]

Hi again, Prad,
In that case, you don’t need the discrete segmentations. Just look at the 
posteriors directly.
Cheers,
/Eugenio


Juan Eugenio Iglesias
ERC Senior Research Fellow
Translational Imaging Group
University College London
http://www.jeiglesias.com
http://cmictig.cs.ucl.ac.uk/


On 22 Mar 2017, at 18:26, Bharadwaj, Pradyumna - (prad) 
mailto:p...@email.arizona.edu>> wrote:

Sorry about that. I should have stated what I was trying to do. I'm trying to 
see if the posterior probability changes when using a certain combination of 
the different T1 and T2 weighted scans that we have in our lab. I thought using 
the binary masks to extract the probabilities as they were the final volumes of 
the subfields would be a better way.


As an example,
when I extract some basic stats on the left CA1 posteriors for one subject, 
these are the values I get,
range: 0.15 to 1, with a mean (sd) of 0.245258 (0.335046);

and , when I use the binary mask of the CA1 from lh.hippoSfLabels-T1.v10.mgz 
and then extract the same basic stats, I get,

range: 0.247501 to 1, with a mean (sd) of 0.770796 (0.175752)

Is my approach incorrect ?

Thanks!,
-Prad



From: 
freesurfer-boun...@nmr.mgh.harvard.edu<mailto:freesurfer-boun...@nmr.mgh.harvard.edu>
 
mailto:freesurfer-boun...@nmr.mgh.harvard.edu>>
 on behalf of Iglesias Gonzalez, Eugenio 
mailto:e.igles...@ucl.ac.uk>>
Sent: Wednesday, March 22, 2017 11:06 AM
To: Freesurfer support list
Subject: Re: [Freesurfer] Hippocampal Subfields Posterior Probability

Hi Prad,
The final probabilities are in the posterior files. There’s no need to binarize 
?h.hippoSfLabels if what you’re interested in is the soft segmentations.
Or maybe I’m missing something? What are you exactly trying to do?
Cheers,
/E

Juan Eugenio Iglesias
ERC Senior Research Fellow
Translational Imaging Group
University College London
http://www.jeiglesias.com<http://www.jeiglesias.com/>
http://cmictig.cs.ucl.ac.uk/


On 22 Mar 2017, at 18:02, Bharadwaj, Pradyumna - (prad) 
mailto:p...@email.arizona.edu>> wrote:

Hi Dr. Iglesias,

Thank you for the overview of the labeling rules. I have also tried setting 
WRITE_POSTERIORS to 1 to write out the posteriors.

I had a follow up question about obtaining the probabilities for the final 
subfield labels as available in the ?h.hippoSfLabels-T1.v10.mgz

I use mri_binarize on ?h.hippoSfLabels-T1.v10.mgz to obtain binary masks for 
each subfield, and then used these masks with their respective posteriors to 
obtain the distributions.

Is this procedure correct or is there a better way ?

Thanks,
-Prad

From: 
freesurfer-boun...@nmr.mgh.harvard.edu<mailto:freesurfer-boun...@nmr.mgh.harvard.edu>
 
mailto:freesurfer-boun...@nmr.mgh.harvard.edu>>
 on behalf of Iglesias Gonzalez, Eugenio 
mailto:e.igles...@ucl.ac.uk>>
Sent: Tuesday, March 21, 2017 2:22 PM
To: Freesurfer support list
Subject: Re: [Freesurfer] Hippocampal Subfields Posterior Probability

Dear Prad,
There is a “secret” way of getting the posteriors. You need to set the 
environment variable WRITE_POSTERIORS to 1 before you call recon-all.
In (t)csh:
setenv WRITE_POSTERIORS 1
In bash:
export WRITE_POSTERIORS=1
And then call recon-all -hippocampal-subfields-T1(T2) as usual.

The discrete segmentation picks, for each voxel, the most likely label. The 
posterior of this label might or might not be above 0.5. For instance, if a 
voxel has p=0.4 of being CA1, p=0.3 of being background, and p=0.3 of being 
fimbria, it will be labeled as CA1 (even though p<0.5 for such subfield). Some 
people seem to prefer a 2-stage approach, in which a hippocampal mask is first 
created by selecting the voxels for which p(background)<0.5, and then each 
voxel within that mask is colored with the most likely subfield at that 
location.

I hope this helps!

Cheers,

/Eugenio



Juan Eugenio Iglesias
ERC Senior Research Fellow
Translational Imaging Group
University College London
http://www.jeiglesias.com<http://www.jeiglesias.com/>
http://cmictig.cs.ucl.ac.uk/


On 21 Mar 2017, at 20:09, Bharadwaj, Pradyumna - (prad) 
mailto:p...@email.arizona.edu>> wrote:

Hello Dr. Iglesias,

I'm currently examining the distributions of the posterior probabilities of the 
different hippocampal subfields, and I'm interested in obtaining the 
probability distribution images for the subfields that correspond to the 
volumes output in the subjects text file.

While I can use mri_binarize on ?h.hippoSfLabels-T1.v10.mgz to obtain the 
subfield masks and use them to obtain the posterior probabilities distribution 
after soft segmentation,
is there some other straighforward way to obtain these posterior probabilities 
for the volumes stated in the output text file ?

A follow up question - It appears that the soft segmentation approach 
approximates thresholding the posteriors by a value around 0.5 ? In you

Re: [Freesurfer] Hippocampal Subfields Posterior Probability

[Bharadwaj, Pradyumna - (prad)]

Sorry about that. I should have stated what I was trying to do. I'm trying to 
see if the posterior probability changes when using a certain combination of 
the different T1 and T2 weighted scans that we have in our lab. I thought using 
the binary masks to extract the probabilities as they were the final volumes of 
the subfields would be a better way.


As an example,
when I extract some basic stats on the left CA1 posteriors for one subject, 
these are the values I get,
range: 0.15 to 1, with a mean (sd) of 0.245258 (0.335046);

and , when I use the binary mask of the CA1 from lh.hippoSfLabels-T1.v10.mgz 
and then extract the same basic stats, I get,

range: 0.247501 to 1, with a mean (sd) of 0.770796 (0.175752)

Is my approach incorrect ?

Thanks!,
-Prad



From: freesurfer-boun...@nmr.mgh.harvard.edu 
 on behalf of Iglesias Gonzalez, 
Eugenio 
Sent: Wednesday, March 22, 2017 11:06 AM
To: Freesurfer support list
Subject: Re: [Freesurfer] Hippocampal Subfields Posterior Probability

Hi Prad,
The final probabilities are in the posterior files. There’s no need to binarize 
?h.hippoSfLabels if what you’re interested in is the soft segmentations.
Or maybe I’m missing something? What are you exactly trying to do?
Cheers,
/E

Juan Eugenio Iglesias
ERC Senior Research Fellow
Translational Imaging Group
University College London
http://www.jeiglesias.com
http://cmictig.cs.ucl.ac.uk/


On 22 Mar 2017, at 18:02, Bharadwaj, Pradyumna - (prad) 
mailto:p...@email.arizona.edu>> wrote:

Hi Dr. Iglesias,

Thank you for the overview of the labeling rules. I have also tried setting 
WRITE_POSTERIORS to 1 to write out the posteriors.

I had a follow up question about obtaining the probabilities for the final 
subfield labels as available in the ?h.hippoSfLabels-T1.v10.mgz

I use mri_binarize on ?h.hippoSfLabels-T1.v10.mgz to obtain binary masks for 
each subfield, and then used these masks with their respective posteriors to 
obtain the distributions.

Is this procedure correct or is there a better way ?

Thanks,
-Prad

From: 
freesurfer-boun...@nmr.mgh.harvard.edu<mailto:freesurfer-boun...@nmr.mgh.harvard.edu>
 
mailto:freesurfer-boun...@nmr.mgh.harvard.edu>>
 on behalf of Iglesias Gonzalez, Eugenio 
mailto:e.igles...@ucl.ac.uk>>
Sent: Tuesday, March 21, 2017 2:22 PM
To: Freesurfer support list
Subject: Re: [Freesurfer] Hippocampal Subfields Posterior Probability

Dear Prad,
There is a “secret” way of getting the posteriors. You need to set the 
environment variable WRITE_POSTERIORS to 1 before you call recon-all.
In (t)csh:
setenv WRITE_POSTERIORS 1
In bash:
export WRITE_POSTERIORS=1
And then call recon-all -hippocampal-subfields-T1(T2) as usual.

The discrete segmentation picks, for each voxel, the most likely label. The 
posterior of this label might or might not be above 0.5. For instance, if a 
voxel has p=0.4 of being CA1, p=0.3 of being background, and p=0.3 of being 
fimbria, it will be labeled as CA1 (even though p<0.5 for such subfield). Some 
people seem to prefer a 2-stage approach, in which a hippocampal mask is first 
created by selecting the voxels for which p(background)<0.5, and then each 
voxel within that mask is colored with the most likely subfield at that 
location.

I hope this helps!

Cheers,

/Eugenio



Juan Eugenio Iglesias
ERC Senior Research Fellow
Translational Imaging Group
University College London
http://www.jeiglesias.com<http://www.jeiglesias.com/>
http://cmictig.cs.ucl.ac.uk/


On 21 Mar 2017, at 20:09, Bharadwaj, Pradyumna - (prad) 
mailto:p...@email.arizona.edu>> wrote:

Hello Dr. Iglesias,

I'm currently examining the distributions of the posterior probabilities of the 
different hippocampal subfields, and I'm interested in obtaining the 
probability distribution images for the subfields that correspond to the 
volumes output in the subjects text file.

While I can use mri_binarize on ?h.hippoSfLabels-T1.v10.mgz to obtain the 
subfield masks and use them to obtain the posterior probabilities distribution 
after soft segmentation,
is there some other straighforward way to obtain these posterior probabilities 
for the volumes stated in the output text file ?

A follow up question - It appears that the soft segmentation approach 
approximates thresholding the posteriors by a value around 0.5 ? In your 
opinion, is this value acceptable and have you found similar values in your 
testing ?

Thanks!
-Prad


___
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Freesurfer@nmr.mgh.harvard.edu<mailto:Freesurfer@nmr.mgh.harvard.edu>
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer


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 Partners Compliance HelpLine at
http://www.partn

Re: [Freesurfer] Hippocampal Subfields Posterior Probability

[Iglesias Gonzalez, Eugenio]

Hi Prad,
The final probabilities are in the posterior files. There’s no need to binarize 
?h.hippoSfLabels if what you’re interested in is the soft segmentations.
Or maybe I’m missing something? What are you exactly trying to do?
Cheers,
/E

Juan Eugenio Iglesias
ERC Senior Research Fellow
Translational Imaging Group
University College London
http://www.jeiglesias.com
http://cmictig.cs.ucl.ac.uk/


On 22 Mar 2017, at 18:02, Bharadwaj, Pradyumna - (prad) 
mailto:p...@email.arizona.edu>> wrote:

Hi Dr. Iglesias,

Thank you for the overview of the labeling rules. I have also tried setting 
WRITE_POSTERIORS to 1 to write out the posteriors.

I had a follow up question about obtaining the probabilities for the final 
subfield labels as available in the ?h.hippoSfLabels-T1.v10.mgz

I use mri_binarize on ?h.hippoSfLabels-T1.v10.mgz to obtain binary masks for 
each subfield, and then used these masks with their respective posteriors to 
obtain the distributions.

Is this procedure correct or is there a better way ?

Thanks,
-Prad

From: 
freesurfer-boun...@nmr.mgh.harvard.edu<mailto:freesurfer-boun...@nmr.mgh.harvard.edu>
 
mailto:freesurfer-boun...@nmr.mgh.harvard.edu>>
 on behalf of Iglesias Gonzalez, Eugenio 
mailto:e.igles...@ucl.ac.uk>>
Sent: Tuesday, March 21, 2017 2:22 PM
To: Freesurfer support list
Subject: Re: [Freesurfer] Hippocampal Subfields Posterior Probability

Dear Prad,
There is a “secret” way of getting the posteriors. You need to set the 
environment variable WRITE_POSTERIORS to 1 before you call recon-all.
In (t)csh:
setenv WRITE_POSTERIORS 1
In bash:
export WRITE_POSTERIORS=1
And then call recon-all -hippocampal-subfields-T1(T2) as usual.

The discrete segmentation picks, for each voxel, the most likely label. The 
posterior of this label might or might not be above 0.5. For instance, if a 
voxel has p=0.4 of being CA1, p=0.3 of being background, and p=0.3 of being 
fimbria, it will be labeled as CA1 (even though p<0.5 for such subfield). Some 
people seem to prefer a 2-stage approach, in which a hippocampal mask is first 
created by selecting the voxels for which p(background)<0.5, and then each 
voxel within that mask is colored with the most likely subfield at that 
location.

I hope this helps!

Cheers,

/Eugenio



Juan Eugenio Iglesias
ERC Senior Research Fellow
Translational Imaging Group
University College London
http://www.jeiglesias.com<http://www.jeiglesias.com/>
http://cmictig.cs.ucl.ac.uk/


On 21 Mar 2017, at 20:09, Bharadwaj, Pradyumna - (prad) 
mailto:p...@email.arizona.edu>> wrote:

Hello Dr. Iglesias,

I'm currently examining the distributions of the posterior probabilities of the 
different hippocampal subfields, and I'm interested in obtaining the 
probability distribution images for the subfields that correspond to the 
volumes output in the subjects text file.

While I can use mri_binarize on ?h.hippoSfLabels-T1.v10.mgz to obtain the 
subfield masks and use them to obtain the posterior probabilities distribution 
after soft segmentation,
is there some other straighforward way to obtain these posterior probabilities 
for the volumes stated in the output text file ?

A follow up question - It appears that the soft segmentation approach 
approximates thresholding the posteriors by a value around 0.5 ? In your 
opinion, is this value acceptable and have you found similar values in your 
testing ?

Thanks!
-Prad


___
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https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer


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 Partners Compliance HelpLine at
http://www.partners.org/complianceline . If the e-mail was sent to you in error
but does not contain patient information, please contact the sender and properly
dispose of the e-mail.

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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 Partners Compliance HelpLine at
http://www.partners.org/complianceline . If the e-mail was sent to you in error
but does not contain patient information, please contact the sender and properly
dispose of the e-mail.

___
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The information in this e-mail is intended only for the person to whom it i

Re: [Freesurfer] Hippocampal Subfields Posterior Probability

[Bharadwaj, Pradyumna - (prad)]

Hi Dr. Iglesias,


Thank you for the overview of the labeling rules. I have also tried setting 
WRITE_POSTERIORS to 1 to write out the posteriors.


I had a follow up question about obtaining the probabilities for the final 
subfield labels as available in the ?h.hippoSfLabels-T1.v10.mgz


I use mri_binarize on ?h.hippoSfLabels-T1.v10.mgz to obtain binary masks for 
each subfield, and then used these masks with their respective posteriors to 
obtain the distributions.


Is this procedure correct or is there a better way ?


Thanks,

-Prad


From: freesurfer-boun...@nmr.mgh.harvard.edu 
 on behalf of Iglesias Gonzalez, 
Eugenio 
Sent: Tuesday, March 21, 2017 2:22 PM
To: Freesurfer support list
Subject: Re: [Freesurfer] Hippocampal Subfields Posterior Probability

Dear Prad,
There is a "secret" way of getting the posteriors. You need to set the 
environment variable WRITE_POSTERIORS to 1 before you call recon-all.
In (t)csh:
setenv WRITE_POSTERIORS 1
In bash:
export WRITE_POSTERIORS=1
And then call recon-all -hippocampal-subfields-T1(T2) as usual.

The discrete segmentation picks, for each voxel, the most likely label. The 
posterior of this label might or might not be above 0.5. For instance, if a 
voxel has p=0.4 of being CA1, p=0.3 of being background, and p=0.3 of being 
fimbria, it will be labeled as CA1 (even though p<0.5 for such subfield). Some 
people seem to prefer a 2-stage approach, in which a hippocampal mask is first 
created by selecting the voxels for which p(background)<0.5, and then each 
voxel within that mask is colored with the most likely subfield at that 
location.

I hope this helps!

Cheers,

/Eugenio



Juan Eugenio Iglesias
ERC Senior Research Fellow
Translational Imaging Group
University College London
http://www.jeiglesias.com
http://cmictig.cs.ucl.ac.uk/


On 21 Mar 2017, at 20:09, Bharadwaj, Pradyumna - (prad) 
mailto:p...@email.arizona.edu>> wrote:

Hello Dr. Iglesias,

I'm currently examining the distributions of the posterior probabilities of the 
different hippocampal subfields, and I'm interested in obtaining the 
probability distribution images for the subfields that correspond to the 
volumes output in the subjects text file.

While I can use mri_binarize on ?h.hippoSfLabels-T1.v10.mgz to obtain the 
subfield masks and use them to obtain the posterior probabilities distribution 
after soft segmentation,
is there some other straighforward way to obtain these posterior probabilities 
for the volumes stated in the output text file ?

A follow up question - It appears that the soft segmentation approach 
approximates thresholding the posteriors by a value around 0.5 ? In your 
opinion, is this value acceptable and have you found similar values in your 
testing ?

Thanks!
-Prad


___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu<mailto:Freesurfer@nmr.mgh.harvard.edu>
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer


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 Partners Compliance HelpLine at
http://www.partners.org/complianceline . If the e-mail was sent to you in error
but does not contain patient information, please contact the sender and properly
dispose of the e-mail.

___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer


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 Partners Compliance HelpLine at
http://www.partners.org/complianceline . If the e-mail was sent to you in error
but does not contain patient information, please contact the sender and properly
dispose of the e-mail.

Re: [Freesurfer] Hippocampal Subfields Posterior Probability

[Iglesias Gonzalez, Eugenio]

Dear Prad,
There is a “secret” way of getting the posteriors. You need to set the 
environment variable WRITE_POSTERIORS to 1 before you call recon-all.
In (t)csh:
setenv WRITE_POSTERIORS 1
In bash:
export WRITE_POSTERIORS=1
And then call recon-all -hippocampal-subfields-T1(T2) as usual.

The discrete segmentation picks, for each voxel, the most likely label. The 
posterior of this label might or might not be above 0.5. For instance, if a 
voxel has p=0.4 of being CA1, p=0.3 of being background, and p=0.3 of being 
fimbria, it will be labeled as CA1 (even though p<0.5 for such subfield). Some 
people seem to prefer a 2-stage approach, in which a hippocampal mask is first 
created by selecting the voxels for which p(background)<0.5, and then each 
voxel within that mask is colored with the most likely subfield at that 
location.

I hope this helps!

Cheers,

/Eugenio



Juan Eugenio Iglesias
ERC Senior Research Fellow
Translational Imaging Group
University College London
http://www.jeiglesias.com
http://cmictig.cs.ucl.ac.uk/


On 21 Mar 2017, at 20:09, Bharadwaj, Pradyumna - (prad) 
mailto:p...@email.arizona.edu>> wrote:

Hello Dr. Iglesias,

I'm currently examining the distributions of the posterior probabilities of the 
different hippocampal subfields, and I'm interested in obtaining the 
probability distribution images for the subfields that correspond to the 
volumes output in the subjects text file.

While I can use mri_binarize on ?h.hippoSfLabels-T1.v10.mgz to obtain the 
subfield masks and use them to obtain the posterior probabilities distribution 
after soft segmentation,
is there some other straighforward way to obtain these posterior probabilities 
for the volumes stated in the output text file ?

A follow up question - It appears that the soft segmentation approach 
approximates thresholding the posteriors by a value around 0.5 ? In your 
opinion, is this value acceptable and have you found similar values in your 
testing ?

Thanks!
-Prad


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[Freesurfer] Hippocampal Subfields Posterior Probability

[Bharadwaj, Pradyumna - (prad)]

Hello Dr. Iglesias,


I'm currently examining the distributions of the posterior probabilities of the 
different hippocampal subfields, and I'm interested in obtaining the 
probability distribution images for the subfields that correspond to the 
volumes output in the subjects text file.


While I can use mri_binarize on ?h.hippoSfLabels-T1.v10.mgz to obtain the 
subfield masks and use them to obtain the posterior probabilities distribution 
after soft segmentation,

is there some other straighforward way to obtain these posterior probabilities 
for the volumes stated in the output text file ?


A follow up question - It appears that the soft segmentation approach 
approximates thresholding the posteriors by a value around 0.5 ? In your 
opinion, is this value acceptable and have you found similar values in your 
testing ?


Thanks!

-Prad


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https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer


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 Partners Compliance HelpLine at
http://www.partners.org/complianceline . If the e-mail was sent to you in error
but does not contain patient information, please contact the sender and properly
dispose of the e-mail.