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
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) <prad@email.arizona.edumailto:prad@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.edumailto: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.
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-bounces@nmr.mgh.harvard.edu freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Iglesias Gonzalez, Eugenio e.iglesias@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://cmictig.cs.ucl.ac.uk/
On 21 Mar 2017, at 20:09, Bharadwaj, Pradyumna - (prad) <prad@email.arizona.edumailto:prad@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.edumailto: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.
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) <prad@email.arizona.edumailto:prad@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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu <freesurfer-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Iglesias Gonzalez, Eugenio <e.iglesias@ucl.ac.ukmailto:e.iglesias@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.comhttp://www.jeiglesias.com/ http://cmictig.cs.ucl.ac.uk/
On 21 Mar 2017, at 20:09, Bharadwaj, Pradyumna - (prad) <prad@email.arizona.edumailto:prad@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.edumailto: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.edumailto: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.
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: 0.000015 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-bounces@nmr.mgh.harvard.edu freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Iglesias Gonzalez, Eugenio e.iglesias@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://cmictig.cs.ucl.ac.uk/
On 22 Mar 2017, at 18:02, Bharadwaj, Pradyumna - (prad) <prad@email.arizona.edumailto:prad@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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu <freesurfer-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Iglesias Gonzalez, Eugenio <e.iglesias@ucl.ac.ukmailto:e.iglesias@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.comhttp://www.jeiglesias.com/ http://cmictig.cs.ucl.ac.uk/
On 21 Mar 2017, at 20:09, Bharadwaj, Pradyumna - (prad) <prad@email.arizona.edumailto:prad@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.edumailto: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.edumailto: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.
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) <prad@email.arizona.edumailto:prad@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: 0.000015 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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu <freesurfer-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Iglesias Gonzalez, Eugenio <e.iglesias@ucl.ac.ukmailto:e.iglesias@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.comhttp://www.jeiglesias.com/ http://cmictig.cs.ucl.ac.uk/
On 22 Mar 2017, at 18:02, Bharadwaj, Pradyumna - (prad) <prad@email.arizona.edumailto:prad@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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu <freesurfer-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Iglesias Gonzalez, Eugenio <e.iglesias@ucl.ac.ukmailto:e.iglesias@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.comhttp://www.jeiglesias.com/ http://cmictig.cs.ucl.ac.uk/
On 21 Mar 2017, at 20:09, Bharadwaj, Pradyumna - (prad) <prad@email.arizona.edumailto:prad@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.edumailto: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.edumailto: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.edumailto: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.
Great! Thank you for taking that time to clarify that.
-Prad
________________________________ From: freesurfer-bounces@nmr.mgh.harvard.edu freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Iglesias Gonzalez, Eugenio e.iglesias@ucl.ac.uk 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) <prad@email.arizona.edumailto:prad@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: 0.000015 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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu <freesurfer-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Iglesias Gonzalez, Eugenio <e.iglesias@ucl.ac.ukmailto:e.iglesias@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.comhttp://www.jeiglesias.com/ http://cmictig.cs.ucl.ac.uk/
On 22 Mar 2017, at 18:02, Bharadwaj, Pradyumna - (prad) <prad@email.arizona.edumailto:prad@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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu <freesurfer-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Iglesias Gonzalez, Eugenio <e.iglesias@ucl.ac.ukmailto:e.iglesias@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.comhttp://www.jeiglesias.com/ http://cmictig.cs.ucl.ac.uk/
On 21 Mar 2017, at 20:09, Bharadwaj, Pradyumna - (prad) <prad@email.arizona.edumailto:prad@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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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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Bharadwaj, Pradyumna - (prad) -
Iglesias Gonzalez, Eugenio