Freesurfer August 2011

freesurfer@nmr.mgh.harvard.edu

124 participants
212 discussions

Intensity normalization parameters to fix dura included in pial surface
by Martina Ly 24 Aug '11

24 Aug '11

Hello freesurfers, Dura is being included in the pial surface of the superior section of the brain in about 80% of the subjects (about 200) that I'm processing in fs version 5.1 on Mac OS X 10.6.8. The T1s were acquired on a GE 3T scanner. It takes too much time to manually edit the dura and I would not like to do so much manual intervention on the other 2 time points. Adjusting the watershed parameters and the -gcut flag did not help. Would I be able to adjust nu_correct or mri_normalize (the intensity normalization steps prior to skull stripping)? I'm also thinking of using another intensity correction software (i.e. unicorr) to put back into the freesurfer pipeline but I would prefer a flag or parameter I can adjust within fs. I've attached a tkmedit and a pial image (flattening of gyri due to including dura). Any suggestions would be appreciated! Best, Martina

1 0

.curv
by Antonella Cappelletti 24 Aug '11

24 Aug '11

Hi, I need a sulcal map and I saw that freesurfer can generate .curv and .sulc files that have this information. It is possibile to convert these formats into a vtk one, or to join the information of a .curv file format whit a volumetric one, having a volumetric file with the infomations of a .curv file? -- Antonella

2 3

Brain volume in FreeSurfer analysis
by zuzana nedelska 24 Aug '11

24 Aug '11

Hello, I have a question about calculating brain volume (in mm3) when performing recon-all. Do I take brainseg volume in the analysis stream line as subject's brain volume (in mm3)? Thank you for reply.

3 4

cortical thickness version 3.02 vs 4.5
by Rune Thormodsen 23 Aug '11

23 Aug '11

Hi, We are concerned about differences of cortical thickness when we process the same scans in freesurfer 4.5 and 3.02. We have attached an excel spreadsheet of the differences in thickness between 4.5 and 3.02 using the mean thickness of parcellations of both versions in both hemispheres. The difference in the paracellations vary from 3-11% between the versions. Are these findings reliable and explainable in choosing freesurfer 4.5 as our final version. Any comment are greatly appreciated, Thanks! Rune

2 1

the Subcortical Segmentation and the Cortical Parcellation
by Kenichiro Tanaka 23 Aug '11

23 Aug '11

Hello All, I have a question about "segmentation" and "parcellation". What is the difference between the subcortical segmentation and the cortical parcellation? Especially I do not understand the difference between subcortical and cortical and between segmentation and parcellation. I tried to read FreeSurfer Wiki, but I did not understand it well. Could you tell me it? Thanks. Kenichiro Tanaka.

4 3

cortical thickness
by Ed Gronenschild 23 Aug '11

23 Aug '11

Hi, How do you compute the cortical thickness for each structure as listed in the ?h.aparc.stats file? Is it equal to the thickness for each vertex averaged over all vertices within each structure? Ed

1 0

Grad_unwarp not working properly
by Martijn Cloos 23 Aug '11

23 Aug '11

Dear all, I'm trying to use grad_unwarp to correct for the gradient nonlinearities. Construction of the .coef and .gwv files from the .grad file provided by Siemens seems to work fine. Infact, "grad_warp -i in.mhz -o out.mgz -u sonata" also runs without any problem. However, the image obtained looks like a field map of the gradients not the corrected image. Did I miss some important step? Thanks in advance, Martijn

1 0

Re: [Freesurfer] Coordinate transformations from orig/001.mgz to T1.mgz
by Douglas N Greve 22 Aug '11

22 Aug '11

Do you just need a vox2vox that goes from the conformed space back to the original dicom space? That's pretty easy, if that's the case. doug Aapo Nummenmaa wrote: > Hi Doug, > > thanks for the reply. I have looked at the document and know > approximately how things are defined. > Our target TMS coordinate system is defined in terms of the original > DICOM data and is > "LSA", independent of how the data was acquired (let's say it is "PIL"). > I know naturally how to go from "PIL" to "RAS" to "LSA" and so forth > within this volume. > I operate with MATLAB, so when I load this stuff in, I can see if the > column-row-slice order actually is > "LIA", "PIL" or whatnot "mri_info" says. > > But once the original data is processed by FS, to my understanding the > data is conformed to be > isotropic 1 mm voxels with matrix 256x256x256 and orientation "LIA". > So Tommi's question is can we incorporate > this resampling procedure to obtain some kind of > voxel-to-voxel transformation directly. It should be straightforward > in principle, > but I'm not sure what FreeSurfer exactly does during this resampling > step. Assuming isotropic 1mm voxels to begin with, it seems > to zero-fill the volume keeping the center of the FOV fixed. > > For now, I have just "reverse engineered" the voxel to voxel (or > rather XYZ to XYZ) transformation by identifying > same anatomical landmarks in the TMS and FreeSurfer coordinates. I > guess we can also use > "bbregister" to co-register the original data with "orig.mgz" (or > "T1.mgz") as an /ad hoc /solution. > > But of course, as Tommi pointed out, if the transformation can be > figured out directly, that would be the > nicest option. > > Thanks, > > -Aapo > > > > > > > On Aug 22, 2011, at 11:55 AM, Douglas N Greve wrote: > >> Hi Tommi, have you looked at this document? >> http://www.freesurfer.net/fswiki/CoordinateSystems?action=AttachFile&do=get… >> <http://www.freesurfer.net/fswiki/CoordinateSystems?action=AttachFile&do=get…> >> >> doug >> >> raij(a)nmr.mgh.harvard.edu wrote: >>> Hi, >>> >>> We (Aapo Nummenmaa and I) are developing cross-platform software that >>> would allow translating third-party coordinates back and forth with >>> Freesurfer segmentations. >>> >>> Our example structural image is MEMPRAGE_4e_p2_1mm_iso (1 mm isotropic, >>> 192 sagittal slices, T1 weighting). >>> >>> Our third-party system (TMS-navigator Nexstim NBS) uses DICOM/nifti with >>> origin (0,0,0) at right posterior inferior corner of the stack with >>> x=R-L >>> y=I-S z=P-A. >>> >>> Our goal is to relate the Nexstim NBS coordinates to these two images: >>> 1. $SUBJECTS_DIR/$SUBJECT/mri/orig/001.mgz (not altered by recon-all) >>> 2. $SUBJECTS_DIR/$SUBJECT/mri/T1.mgz (altered by recon-all) >>> >>> For (1) above, "Volume Index" in tkmedit looks like this: origin (0,0,0) >>> is at right anterior superior corner of the stack with x=A-P y=S-I >>> z=R-L. >>> Max values in tkmedit display were (255,243,191). The acquisition >>> had 192 >>> sagittal slices so the last number makes sense - not sure why the second >>> figure is not 255 (perhaps just a display thing). The orig/001.mgz stack >>> should be exactly the same stack as in the Nexstim NBS image (which is >>> just the plain DICOM), without any resampling or other processing, just >>> the axes have been reshuffled a bit. >>> >>> For (2) above, "Volume Index" in tkmedit looks like this: origin (0,0,0) >>> is at right posterior superior corner of the stack with x=R-L y=S-I >>> z=P-A. >>> Max values in tkmedit display were (255,255,255). This makes things >>> difficult, as we do not know what exactly recon-all did to orig/001.mgz >>> when it converted it into T1.mgz. >>> >>> Our question is this: Is there a deterministic way to go from >>> orig/001.mgz >>> to T1.mgz Volume Index coordinates? It seems that recon-all has at least >>> added sagittal slices to make the T1.mgz stack into a cube (looking at >>> lateral shift between 001.mgz and T1.mgz, I would guess that 32 1-mm >>> slices on both sides (2*32+192=256) were added)... Further, it is not >>> clear if the orig/001.mgz volume has been shifted, rotated, or resampled >>> by recon-all when turning it into T1.mgz. >>> >>> Thank you for the advice! >>> >>> Bests, >>> >>> Tommi & Aapo >>> >>> _______________________________________________ >>> Freesurfer mailing list >>> Freesurfer(a)nmr.mgh.harvard.edu >>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>> >>> >>> >> >> -- >> Douglas N. Greve, Ph.D. >> MGH-NMR Center >> greve(a)nmr.mgh.harvard.edu >> Phone Number: 617-724-2358 Fax: 617-726-7422 >> >> Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting >> FileDrop: www.nmr.mgh.harvard.edu/facility/filedrop/index.html >> >> > -- Douglas N. Greve, Ph.D. MGH-NMR Center greve(a)nmr.mgh.harvard.edu Phone Number: 617-724-2358 Fax: 617-726-7422 Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting FileDrop: www.nmr.mgh.harvard.edu/facility/filedrop/index.html

2 4

cortical thickness in freesurfer 3.02 vs 4.5
by Rune X 22 Aug '11

22 Aug '11

1 0

Unusual findings in regression analyses
by Adam Nitenson 22 Aug '11

22 Aug '11

Hi Doug, We've been running a regression analysis on our subjects, and the results are quite puzzling as they don't seem to sync up with the individual pieces of the regression. The data is taken from the Sternberg memory paradigm, with subjects memorizing groups of 1, 3, 5 and 7 letters. We have looked at imaging data of 1vFix, 3vFix, 5vFix, 7vFix, and then our regression analysis, in theory, we should see areas of significant linear pattern when moving from the activation between 1, 3, 5, and 7 letters. However, in our latest analyses, the regression maps have not been complimenting some of the individual subjects' 1,3,etc vs Fix data. In the attached PDF, there are 2 subjects with their 1vFix, 3vFix, etc maps shown, as well as the regression map in the middle, and as you can see, particularly for the 2nd subject, the regression map just doesn't make sense considering the maps from which it was derived. The third sheet of the excel file plots the ROI values generated from the regression analysis against a calculated slope derived from the funcroi values from 1, 3, 5, and 7 vs Fix. The two outliers in the top left are the subjects we further analyzed in the attached powerpoint (which includes ROI derived values). Another strange occurance is that when making regression maps for sub-groups of approx. 8 subjects, the maps don't seems to match up well with the numbers, but the regression map of all of our subjects together looks great, yet the average ROI derived value is quite low. We've been searching for a few days for a "stupid mistake" that could have caused this, but nothing is popping out. I'm attached the analysis info for the regression analysis as well as an example paradigm file for that analysis (slopepar). We just are not sure why the regression maps and individual subject ROI values are so low consider the rather strong regression effect implied from simply eyeballing the data. I understand that the maps may not always be as strong as anticipated, but they should certainly not show dark negative blue when the pattern is positive. Examples of group commands: isxconcat-sess -sf /cluster/roffman/users/Stable5_PerRun/Subject_Files/9_ActiveFolate_Post_5T -d /cluster/roffman/users/Stable5_PerRun -analysis SIRP_LoadRegression_Stable5 -c Cond2vFix -o /cluster/roffman/users/Stable5_PerRun/August_2011/9_ActiveFolate_Post_5T_TEST "mri_glmfit --y /cluster/roffman/users/Stable5_PerRun/August_2011/9_ActiveFolate_Post_5T_TEST/SIRP_LoadRegression_Stable5/Cond2vFix/lh.ces.nii --fsgd /cluster/roffman/users/fsgd/9_ActiveFolate_Post_5T.fsgd --osgm --glmdir /cluster/roffman/users/Stable5_PerRun/August_2011/9_ActiveFolate_Post_5T_TEST/SIRP_LoadRegression_Stable5/osgm/LH2vFix --surf fsaverage lh --fwhm 4.6 Adam Nitenson, B.S. Brain Genomics Lab Massachusetts General Hospital nitenson(a)nmr.mgh.harvard.edu Phone: 617-643-3215

2 1

← Newer
1
...
4
5
6
7
8
9
10
...
22
Older →

Jump to page:

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

Freesurfer August 2011