Hi,
I am new to freesurfer and I am trying to figure our how to extract 3d masks in native space for the visual cortex (BA 17,18,19) of individual subjects. I have looked at other threads similar to this, but there are still a few things I can't figure out in generating the masks (the conversion to native space should be fine).
1- I ran recon-all and I have V1, V2 and MT labels. My knowledge of brain anatomy is very limited, but if I understand correctly, this equates to BA 17, 18 and V5, so I don't have access to all of B19 (V3, V4 and V5), right?
2- I managed to convert V1, V2 and MT labels to 3d masks using mri_label2vol and it seems to work at first glance when I looked at the generated file with freeView. However, I read in the mailing list that mri_label2vol produces "patchy" volumes and that it is preferable to use mri_aparc2aseg instead. That's what I can't figure out. From what I understand, mri_aparc2aseg aims to map the surface labels of interest to the segmented volumes? I tried doing the following (I altered some file names/paths for readability):
# convert labels to annotation (outputs lh.myAnnot.annot & rh.myAnnot.annot)) mris_label2annot --s <subject> --h lh --l lh.V1.label --l lh.V2.label ---l lh.label --ctab BA.ctab --a annot mris_label2annot --s <subject> --h rh --l rh.V1.label --l rhV2.label ---l rh.label --ctab BA.ctab --a annot
# convert to volume mri_aparc2aseg --s <subject> --annot myAnnot.annot --o lh.asegTest.mgz
When I look at the asegTest.mgz file in freeView, I only see segmented cortical volumes and I can't see anything related to V1, V2 or MT, so I assume that I don't use mri_aparc2aseg correctly, but I can't manage to make it work.
Any help would be appreciated! David
Hi David
what is the annot you are using in mris_label2annot? is it the ?h.BA.annot?
cheers Bruce On Mon, 8 Sep 2014, David Provencher wrote:
Hi,
I am new to freesurfer and I am trying to figure our how to extract 3d masks in native space for the visual cortex (BA 17,18,19) of individual subjects. I have looked at other threads similar to this, but there are still a few things I can't figure out in generating the masks (the conversion to native space should be fine).
1- I ran recon-all and I have V1, V2 and MT labels. My knowledge of brain anatomy is very limited, but if I understand correctly, this equates to BA 17, 18 and V5, so I don't have access to all of B19 (V3, V4 and V5), right?
2- I managed to convert V1, V2 and MT labels to 3d masks using mri_label2vol and it seems to work at first glance when I looked at the generated file with freeView. However, I read in the mailing list that mri_label2vol produces "patchy" volumes and that it is preferable to use mri_aparc2aseg instead. That's what I can't figure out. From what I understand, mri_aparc2aseg aims to map the surface labels of interest to the segmented volumes? I tried doing the following (I altered some file names/paths for readability):
# convert labels to annotation (outputs lh.myAnnot.annot & rh.myAnnot.annot)) mris_label2annot --s <subject> --h lh --l lh.V1.label --l lh.V2.label ---l lh.label --ctab BA.ctab --a annot mris_label2annot --s <subject> --h rh --l rh.V1.label --l rhV2.label ---l rh.label --ctab BA.ctab --a annot
# convert to volume mri_aparc2aseg --s <subject> --annot myAnnot.annot --o lh.asegTest.mgz
When I look at the asegTest.mgz file in freeView, I only see segmented cortical volumes and I can't see anything related to V1, V2 or MT, so I assume that I don't use mri_aparc2aseg correctly, but I can't manage to make it work.
Any help would be appreciated! David
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
p.s. probably you should use the ?h.BA.thresh.annot, which is the annot containing the labels thresholded to have the correct area
cheers Bruce
On Mon, 8 Sep 2014, Bruce Fischl wrote:
Hi David
what is the annot you are using in mris_label2annot? is it the ?h.BA.annot?
cheers Bruce On Mon, 8 Sep 2014, David Provencher wrote:
Hi,
I am new to freesurfer and I am trying to figure our how to extract 3d masks in native space for the visual cortex (BA 17,18,19) of individual subjects. I have looked at other threads similar to this, but there are still a few things I can't figure out in generating the masks (the conversion to native space should be fine).
1- I ran recon-all and I have V1, V2 and MT labels. My knowledge of brain anatomy is very limited, but if I understand correctly, this equates to BA 17, 18 and V5, so I don't have access to all of B19 (V3, V4 and V5), right?
2- I managed to convert V1, V2 and MT labels to 3d masks using mri_label2vol and it seems to work at first glance when I looked at the generated file with freeView. However, I read in the mailing list that mri_label2vol produces "patchy" volumes and that it is preferable to use mri_aparc2aseg instead. That's what I can't figure out. From what I understand, mri_aparc2aseg aims to map the surface labels of interest to the segmented volumes? I tried doing the following (I altered some file names/paths for readability):
# convert labels to annotation (outputs lh.myAnnot.annot & rh.myAnnot.annot)) mris_label2annot --s <subject> --h lh --l lh.V1.label --l lh.V2.label ---l lh.label --ctab BA.ctab --a annot mris_label2annot --s <subject> --h rh --l rh.V1.label --l rhV2.label ---l rh.label --ctab BA.ctab --a annot
# convert to volume mri_aparc2aseg --s <subject> --annot myAnnot.annot --o lh.asegTest.mgz
When I look at the asegTest.mgz file in freeView, I only see segmented cortical volumes and I can't see anything related to V1, V2 or MT, so I assume that I don't use mri_aparc2aseg correctly, but I can't manage to make it work.
Any help would be appreciated! David
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Hi Bruce,
First of all, thanks for the reply! There was a typo in my initial question, so I rewrote it to make it clearer :
# convert labels to annotation (outputs lh.myAnnot.annot & rh.myAnnot.annot) mris_label2annot --s <subject> --h lh --l lh.V1.label --l lh.V2.label --l lh.label --ctab BA.ctab --a myAnnot mris_label2annot --s <subject> --h rh --l rh.V1.label --l rh.V2.label --l rh.label --ctab BA.ctab --a myAnnot
# convert ?h.myAnnot.annot files to volume mri_aparc2aseg --s <subject> --annot myAnnot.annot --o mySeg.mgz
I had not noticed the ?h.BA.annot and ?h.BA.thresh.annot files so I was trying to create an annotation with the labels I was interested in (V1, V2, MT). Maybe I misunderstood what an annotation is, but I thought it was just a collection of labels. I'm not sure what the difference is between .thresh and "not .thresh" labels. Anyway, whether I run the code above or just the following :
# convert ?h.BA.annot to volume mri_aparc2aseg --s <subject> --annot BA --o BAseg.mgz
when I open the .mgz file in freeview, something is obviously wrong (see https://www.dropbox.com/s/evthp4sx40azost/BAseg.png?dl=0 and https://www.dropbox.com/s/s5s7wcwywlaq68o/mySeg.png?dl=0). In comparison, when I convert either the ?h.myAnnot.annot or ?h.BA.annot files using mri_label2vol, it seems fine (see https://www.dropbox.com/s/avo1ot8bitbaeeo/BAlabels.png?dl=0).
regards, David
On 14-09-08 10:37 AM, Bruce Fischl wrote:
p.s. probably you should use the ?h.BA.thresh.annot, which is the annot containing the labels thresholded to have the correct area
cheers Bruce
On Mon, 8 Sep 2014, Bruce Fischl wrote:
Hi David
what is the annot you are using in mris_label2annot? is it the ?h.BA.annot?
cheers Bruce On Mon, 8 Sep 2014, David Provencher wrote:
Hi,
I am new to freesurfer and I am trying to figure our how to extract 3d masks in native space for the visual cortex (BA 17,18,19) of individual subjects. I have looked at other threads similar to this, but there are still a few things I can't figure out in generating the masks (the conversion to native space should be fine).
1- I ran recon-all and I have V1, V2 and MT labels. My knowledge of brain anatomy is very limited, but if I understand correctly, this equates to BA 17, 18 and V5, so I don't have access to all of B19 (V3, V4 and V5), right?
2- I managed to convert V1, V2 and MT labels to 3d masks using mri_label2vol and it seems to work at first glance when I looked at the generated file with freeView. However, I read in the mailing list that mri_label2vol produces "patchy" volumes and that it is preferable to use mri_aparc2aseg instead. That's what I can't figure out. From what I understand, mri_aparc2aseg aims to map the surface labels of interest to the segmented volumes? I tried doing the following (I altered some file names/paths for readability):
# convert labels to annotation (outputs lh.myAnnot.annot & rh.myAnnot.annot)) mris_label2annot --s <subject> --h lh --l lh.V1.label --l lh.V2.label ---l lh.label --ctab BA.ctab --a annot mris_label2annot --s <subject> --h rh --l rh.V1.label --l rhV2.label ---l rh.label --ctab BA.ctab --a annot
# convert to volume mri_aparc2aseg --s <subject> --annot myAnnot.annot --o lh.asegTest.mgz
When I look at the asegTest.mgz file in freeView, I only see segmented cortical volumes and I can't see anything related to V1, V2 or MT, so I assume that I don't use mri_aparc2aseg correctly, but I can't manage to make it work.
Any help would be appreciated! David
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
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.
Hi David - On the difference between .thresh and "not .thresh" labels: The BA labels come from averaging histologically derived labels from a set of post mortem brains. The non-thresholded version is just the sum of the corresponding labels from the different brains in fsaverage space. So vertices are included even if only one of the brains had their BA in that vertex, which means that these labels are going to be rather large. In the thresholded version, a threshold has been applied to the average BA label, to make it have an area as close as possible to the average area of the individual BA labels. I hope this makes sense.
a.y
On Mon, 8 Sep 2014, David Provencher wrote:
Hi Bruce,
First of all, thanks for the reply! There was a typo in my initial question, so I rewrote it to make it clearer :
# convert labels to annotation (outputs lh.myAnnot.annot & rh.myAnnot.annot) mris_label2annot --s <subject> --h lh --l lh.V1.label --l lh.V2.label --l lh.label --ct ab BA.ctab --a myAnnot mris_label2annot --s <subject> --h rh --l rh.V1.label --l rh.V2.label --l rh.label --ct ab BA.ctab --a myAnnot
# convert ?h.myAnnot.annot files to volume mri_aparc2aseg --s <subject> --annot myAnnot.annot --o mySeg.mgz
I had not noticed the ?h.BA.annot and ?h.BA.thresh.annot files so I was trying to create an annotation with the labels I was interested in (V1, V2, MT). Maybe I misunderstood what an annotation is, but I thought it was just a collection of labels. I'm not sure what the difference is between .thresh and "not .thresh" labels. Anyway, whether I run the code above or just the following :
# convert ?h.BA.annot to volume mri_aparc2aseg --s <subject> --annot BA --o BAseg.mgz
when I open the .mgz file in freeview, something is obviously wrong (see https://www.dropbox.com/s/evthp4sx40azost/BAseg.png?dl=0 and https://www.dropbox.com/s/s5s7wcwywlaq68o/mySeg.png?dl=0). In comparison, when I convert either the ?h.myAnnot.annot or ?h.BA.annot files using mri_label2vol, it seems fine (see https://www.dropbox.com/s/avo1ot8bitbaeeo/BAlabels.png?dl=0).
regards, David
On 14-09-08 10:37 AM, Bruce Fischl wrote:
p.s. probably you should use the ?h.BA.thresh.annot, which is the annot containing the labels thresholded to have the correct area
cheers Bruce
On Mon, 8 Sep 2014, Bruce Fischl wrote:
Hi David
what is the annot you are using in mris_label2annot? is it the ?h.BA.annot?
cheers Bruce On Mon, 8 Sep 2014, David Provencher wrote:
Hi,
I am new to freesurfer and I am trying to figure our how to extract 3d masks in native space for the visual cortex (BA 17,18,19) of individual subjects. I have looked at other threads similar to this, but there are still a few things I can't figure out in generating the masks (the conversion to native space should be fine).
1- I ran recon-all and I have V1, V2 and MT labels. My knowledge of brain anatomy is very limited, but if I understand correctly, this equates to BA 17, 18 and V5, so I don't have access to all of B19 (V3, V4 and V5), right?
2- I managed to convert V1, V2 and MT labels to 3d masks using mri_label2vol and it seems to work at first glance when I looked at the generated file with freeView. However, I read in the mailing list that mri_label2vol produces "patchy" volumes and that it is preferable to use mri_aparc2aseg instead. That's what I can't figure out. From what I understand, mri_aparc2aseg aims to map the surface labels of interest to the segmented volumes? I tried doing the following (I altered some file names/paths for readability):
# convert labels to annotation (outputs lh.myAnnot.annot & rh.myAnnot.annot)) mris_label2annot --s <subject> --h lh --l lh.V1.label --l lh.V2.label ---l lh.label --ctab BA.ctab --a annot mris_label2annot --s <subject> --h rh --l rh.V1.label --l rhV2.label ---l rh.label --ctab BA.ctab --a annot
# convert to volume mri_aparc2aseg --s <subject> --annot myAnnot.annot --o lh.asegTest.mgz
When I look at the asegTest.mgz file in freeView, I only see segmented cortical volumes and I can't see anything related to V1, V2 or MT, so I assume that I don't use mri_aparc2aseg correctly, but I can't manage to make it work.
Any help would be appreciated! David
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
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.
Thanks for the reply Anastasia, that makes it more clear.
I realized that I was confused due to my inexperience with freesurfer and was using the wrong approach. I did not realize I could simply use the segmented volumes in aseg.mgz corresponding to the visual cortex using http://ftp.nmr.mgh.harvard.edu/fswiki/CorticalParcellation as a guideline.
thanks, David
On 14-09-08 12:39 PM, Anastasia Yendiki wrote:
Hi David - On the difference between .thresh and "not .thresh" labels: The BA labels come from averaging histologically derived labels from a set of post mortem brains. The non-thresholded version is just the sum of the corresponding labels from the different brains in fsaverage space. So vertices are included even if only one of the brains had their BA in that vertex, which means that these labels are going to be rather large. In the thresholded version, a threshold has been applied to the average BA label, to make it have an area as close as possible to the average area of the individual BA labels. I hope this makes sense.
a.y
On Mon, 8 Sep 2014, David Provencher wrote:
Hi Bruce,
First of all, thanks for the reply! There was a typo in my initial question, so I rewrote it to make it clearer :
# convert labels to annotation (outputs lh.myAnnot.annot & rh.myAnnot.annot) mris_label2annot --s <subject> --h lh --l lh.V1.label --l lh.V2.label --l lh.label --ct ab BA.ctab --a myAnnot mris_label2annot --s <subject> --h rh --l rh.V1.label --l rh.V2.label --l rh.label --ct ab BA.ctab --a myAnnot
# convert ?h.myAnnot.annot files to volume mri_aparc2aseg --s <subject> --annot myAnnot.annot --o mySeg.mgz
I had not noticed the ?h.BA.annot and ?h.BA.thresh.annot files so I was trying to create an annotation with the labels I was interested in (V1, V2, MT). Maybe I misunderstood what an annotation is, but I thought it was just a collection of labels. I'm not sure what the difference is between .thresh and "not .thresh" labels. Anyway, whether I run the code above or just the following :
# convert ?h.BA.annot to volume mri_aparc2aseg --s <subject> --annot BA --o BAseg.mgz
when I open the .mgz file in freeview, something is obviously wrong (see https://www.dropbox.com/s/evthp4sx40azost/BAseg.png?dl=0 and https://www.dropbox.com/s/s5s7wcwywlaq68o/mySeg.png?dl=0). In comparison, when I convert either the ?h.myAnnot.annot or ?h.BA.annot files using mri_label2vol, it seems fine (see https://www.dropbox.com/s/avo1ot8bitbaeeo/BAlabels.png?dl=0).
regards, David
On 14-09-08 10:37 AM, Bruce Fischl wrote:
p.s. probably you should use the ?h.BA.thresh.annot, which is the annot containing the labels thresholded to have the correct area
cheers Bruce
On Mon, 8 Sep 2014, Bruce Fischl wrote:
Hi David
what is the annot you are using in mris_label2annot? is it the ?h.BA.annot?
cheers Bruce On Mon, 8 Sep 2014, David Provencher wrote:
Hi,
I am new to freesurfer and I am trying to figure our how to extract 3d masks in native space for the visual cortex (BA 17,18,19) of individual subjects. I have looked at other threads similar to this, but there are still a few things I can't figure out in generating the masks (the conversion to native space should be fine).
1- I ran recon-all and I have V1, V2 and MT labels. My knowledge of brain anatomy is very limited, but if I understand correctly, this equates to BA 17, 18 and V5, so I don't have access to all of B19 (V3, V4 and V5), right?
2- I managed to convert V1, V2 and MT labels to 3d masks using mri_label2vol and it seems to work at first glance when I looked at the generated file with freeView. However, I read in the mailing list that mri_label2vol produces "patchy" volumes and that it is preferable to use mri_aparc2aseg instead. That's what I can't figure out. From what I understand, mri_aparc2aseg aims to map the surface labels of interest to the segmented volumes? I tried doing the following (I altered some file names/paths for readability):
# convert labels to annotation (outputs lh.myAnnot.annot & rh.myAnnot.annot)) mris_label2annot --s <subject> --h lh --l lh.V1.label --l lh.V2.label ---l lh.label --ctab BA.ctab --a annot mris_label2annot --s <subject> --h rh --l rh.V1.label --l rhV2.label ---l rh.label --ctab BA.ctab --a annot
# convert to volume mri_aparc2aseg --s <subject> --annot myAnnot.annot --o lh.asegTest.mgz
When I look at the asegTest.mgz file in freeView, I only see segmented cortical volumes and I can't see anything related to V1, V2 or MT, so I assume that I don't use mri_aparc2aseg correctly, but I can't manage to make it work.
Any help would be appreciated! David
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
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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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freesurfer@nmr.mgh.harvard.edu