Freesurfer

freesurfer@nmr.mgh.harvard.edu

17 participants
30086 discussions

MRI Smoothing Edits
by Isaiah C. Smith 15 Aug '14

15 Aug '14

Hello Everyone, I am having a problem with the output of recon-all. T1 (shown below) has in the coronal view some noise in the images, and as a result, when I create head surfaces, there are bumps covering the head’s surface (scalp). Is there a way to effectively smooth this noise. The brain also has a strange output as well. [cid:C3CB0C8F-1A58-4753-B103-256D633677AB@host.ucla.edu] [cid:D7584A00-BC5A-4F2A-8A0A-2DCDC4D09B5D@host.ucla.edu] Isaiah Smith

1 0

language questions+
by Krieger, Donald N. 15 Aug '14

15 Aug '14

segmentation vs parcellation: Segmentation appears to mean identifying and assigning voxels to a label which maps to a gross structure like thalamus, left cortex, etc. Parcellation appears to mean the same but for mappings at higher resolution, e.g. L V1. Is this correct? surface vs volume: My questions here arise from differences in the results of extracting labels when using mri_cor2label vs mri_annotation2label. Spot checks of mri_cor2label results show sets of pixels on a 1 mm grid which fill the volume associated with the label. I have been assuming that this is "volume" although volume also refers to what is captured in the .mgz files. Spot checks of mri_annotation2label results show sets of pixels which appear to delineate boundaries or "surfaces" of the gray matter (--surface orig), white matter ( --surface white) or pia (--surface pial). There appears to a similar switch in the help text for mri_cor2label, i.e. -surf subject hemi <surf>, but it appears to specify the nature of the input rather than that of the output as does the -surface switch in mri_annotation2label. This leads to my next question regarding the input "volume" but first, is what I've said correct so far? An addition concern that I have is that "surface" may be used in reference to a projection onto the sphere. input volumes: Here I have only tried the .mgz files contained in directory ${FREESURFER_HOME}/subjects/NNN/mri . Which of these files are useful as input to mri_cor2label for outputting .label files that are likely to accurately fill the structures to which the label corresponds? What I mean here is which ones represent the end-points of a processing stream and which ones are intermediates? I understand that the intermediates are likely useful given that they are being saved in the standard processing streams. If I load them into freeview, specify the standard color map, and place the cursor on the cerebellum, I can see which ones give the right answer, e.g. aparc.a2009, wmparc, aparc+aseg, aseg.auto, and which don't, e.g. filled, wm.seg, wm, rh.ribbin, brain, brain.finalsurfs, T1, orig (of course). But "filled", for instance, does appear to provide a good segementation of the left and right supra-tentorial white matter although the colors (right=127; left=255) do not map to those names in the standard color table. Regards, Don Don Krieger, Ph.D. Department of Neurological Surgery University of Pittsburgh (412)648-9654 Office (412)521-4431 Cell/Text

2 2

Sniffing dialect of qdec table in asegstats2table
by Bernardoni, Fabio 15 Aug '14

15 Aug '14

Dear all, I am trying to perform a longitudinal lme analysis using freesurfer 5.3.0. For qdec tables with many columns the asegstats2table (and similarly aparcstats2table) commands fail with error message: asegstats2table --qdec-long ./qdec/long.qdec.table.dat --delimiter space --meas volume --stats aseg.stats --tablefile ./measures/lme.aseg.table.txt SUBJECTS_DIR : /sw/global/applications/freesurfer/5.3.0/x86_64/subjects Traceback (most recent call last): File "/sw/global/applications/freesurfer/5.3.0/x86_64/bin/asegstats2table", line 514, in <module> subj_listoftuples = assemble_inputs(options) File "/sw/global/applications/freesurfer/5.3.0/x86_64/bin/asegstats2table", line 316, in assemble_inputs dialect = csv.Sniffer().sniff(f.read(1024)) File "/home/dgeisler/env/lib/python2.7/csv.py", line 184, in sniff raise Error, "Could not determine delimiter" _csv.Error: Could not determine delimiter A solution in my case is to change the line: dialect = csv.Sniffer().sniff(f.read(1024)) to: dialect = csv.Sniffer().sniff(f.read(2048)) Namely the snifffer needs a larger chunk of file to be able to determine the delimiter, in my case. However I think it would be good if one could give the delimiter of the infile as an option from command line. If I have correctly understood the --delimiter option available so far is for the output file, which I called ./measures/lme.aseg.table.txt . Cheers, Fabio Dr. Fabio Bernardoni wiss. Mitarbeiter Klinik und Poliklinik für Kinder- und Jugendpsychiatrie und -psychotherapie Tel. +49 (0)351 458-5245 Fax +49 (0)351 458-7206 Universitätsklinikum Carl Gustav Carus an der Technischen Universität Dresden Anstalt des öffentlichen Rechts des Freistaates Sachsen Fetscherstraße 74, 01307 Dresden http://www.uniklinikum-dresden.de Vorstand: Prof. Dr. med. D. M. Albrecht (Sprecher), Wilfried E. B. Winzer Vorsitzender des Aufsichtsrates: Prof. Dr. med. Peter C. Scriba USt.-IDNr.: DE 140 135 217, St.-Nr.: 203 145 03113

1 0

mri_surfcluster for FEAT cluster maxima
by Milde, Christopher 14 Aug '14

14 Aug '14

Dear Freesurfers, I’m struggling with finding a way of getting a table of the cluster maxima of FEAT functional data registered to (reg-feat2anat) and resampled to (feat2surf) reconstructed surfaces. I want to extract cluster maxima for single subjects but preferentially NOT in fsaverage group space. The command mri_surfcluster seems to be quite promising for this purpose. Specifically the summary file with the VtxMax But, seemingly I use the wrong input file (-in) for the FEAT functional data (Error wrong type for mghRead). 1.) Is it at all possible to read resampled Feat data with mri_surfcluster? 2.) is it a prerequisite to run mri_glmfit as suggested in https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/FslGroupFeat (I do not want to perform analysis in group space) I'm very thankful for advice Sincerely yours, Chris $ mri_surfcluster --subject PM_02173_inflation --in PM_02173_inflation/ML_us.feat/stats/zstat1.mgh --hemi lh --surf smoothwm --thmin 2 --thmax inf --sign pos --minarea 15 --annot aparc thsign = pos, id = 1 version $Id: mri_surfcluster.c,v 1.51.2.3 2012/05/31 22:10:05 greve Exp $ hemi = lh srcid = PM_02173_inflation/ML_us.feat/stats/zstat1.mgh srcsubjid = PM_02173_inflation srcsurf = smoothwm srcframe = 0 thsign = pos thmin = 2 thmax = inf fdr = -1 minarea = 15 xfmfile = talairach.xfm nth = -1 subjectsdir = /home/christopher/Desktop/freesurfer/subjects FixMNI = 1 ------------- XFM matrix (RAS2RAS) --------------- /home/christopher/Desktop/freesurfer/subjects/PM_02173_inflation/mri/transforms/talairach.xfm 1.127 -0.010 -0.020 0.954; 0.005 0.993 0.048 -16.639; 0.017 -0.052 1.162 -15.969; 0.000 0.000 0.000 1.000; ---------------------------------------------------- Reading source surface /home/christopher/Desktop/freesurfer/subjects/PM_02173_inflation/surf/lh.smoothwm Done reading source surface Reading annotation /home/christopher/Desktop/freesurfer/subjects/PM_02173_inflation/label/lh.aparc.annot reading colortable from annotation file... colortable with 36 entries read (originally /autofs/space/terrier_001/users/nicks/freesurfer/average/colortable_desikan_killiany.txt) Computing metric properties Loading source values mghRead(PM_02173_inflation/ML_us.feat/stats/zstat1.mgh, -1): could not open file ERROR: could not read PM_02173_inflation/ML_us.feat/stats/zstat1.mgh as type

3 3

group analysis in specific ROI
by Mürner-Lavanchy, Ines 14 Aug '14

14 Aug '14

Dear FS experts, I would like to do a group analysis, not over a whole hemisphere, but only whithin a ROI, which I define by myself. Following a description which I found in the list (https://mail.nmr.mgh.harvard.edu/pipermail//freesurfer/2010-January/013220.…) I painted a ROI, and ran mri_glmfit with this ROI in the --label option. When I try to display the results in freewiev, the significance is still displayed for the whole left hemisphere. What am I doing wrong? Thank you very much for your help, Ines

2 1

(no subject)
by Mürner-Lavanchy, Ines 14 Aug '14

14 Aug '14

Dear FS experts,

1 0

a few short confirmatory questions
by Krieger, Donald N. 13 Aug '14

13 Aug '14

mri_annotation2label enables extraction of vectors from .annot files to .label files, one file per label. One may choose orig, white, or pial vectors. (1) orig vectors are on the cortical surface. The gray scale value for each of these is that of gray matter, correct? And these are inside the pia and outside "white," correct? (2) white vectors are at the surface of the white matter just below the "orig" layer, correct? Their gray scale value is that of white matter, correct? Thanks, Don

4 7

Regenerating Pial Surfaces
by Matthew Clem 13 Aug '14

13 Aug '14

Hi FreeSurfers, I have gone through correcting pial surfaces for one subject, and ran the script to regenerate the surfaces: recon-all -autorecon-pial -subjid 1 After running without error, it appears the pial surfaces have not changed at all. Does FS overwrite the previous lh.pial and rh.pial files, or are new files created with the regenerated surfaces? I have searched the machine and have not found any new files, unless they are hidden somewhere I am unaware of. Thanks, Matt ________________________________ UT Southwestern Medical Center The future of medicine, today.

1 0

occipital lobe WM errors
by Walton, Matt 13 Aug '14

13 Aug '14

Hello Freesurfer team, I've used freesurfer to segment (recon-all) approximately 30 different subjects from a study. I've noticed that a large number of these subjects have a misclassification of the white and pial boundaries in the occipital lobe (such that grey matter is being classified as white matter). I believe this problem is originating from my scanner and original data. I'm acquiring a T1W BRAVO sequence on a GE Discovery 750w 3T scanner, using a 32 channel phased array head coil. For many subjects, this acquistion gives intensity inhomogeneity in the occipital lobe. I've begun using a GE based correction technique (PURE) on the images, and it appears to improve the intensity in the occipital lobe, but Freesurfer is still frequently misclassifying. I'm wondering what would be the best way to edit the data. I've often tried to edit the wm.vol, but this doesn't seem to fix anything. For the most part, the wm.vol is correct to begin with, but the wm cutting line isn't segmenting with the wm.vol. I've also tried to add control points but this doesn't seem to improve anything either. I've attached an image which I hope will further explain my problems. Thanks for any help

5 32

quick pointer: tool to extract gray/white contrast vectors from [lr]h.w-g.pct.mgh
by Krieger, Donald N. 13 Aug '14

13 Aug '14

What is the tool to extract the contrast vectors from surf/[ lr]h.w-g.pct.mgh ? Thanks, Don

3 6

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