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3D graphics card and blade systems
by Anderson Winkler 13 Jan '09

13 Jan '09

4 6

Segmentation fault - mris_make_surfaces
by Adrian Williams 13 Jan '09

13 Jan '09

Dear all Came across a segmentation fault while running recon-all, specifically during mris_make_surfaces... Output pasted below... Any ideas/help greatly appreciated! Adrian. -- Adrian L. Williams, PhD Centre for Cognition & Neuroimaging Brunel University Uxbridge Middlesex UB8 3PH #-------------------------------------------- #@# Make Final Surf rh Sun Jan 11 09:11:39 GMT 2009 /Volumes/DataDisk/freesurf/adrian/scripts \n mris_make_surfaces -noaparc -mgz -T1 brain.finalsurfs adrian rh \n not using aparc to prevent surfaces crossing the midline INFO: assuming MGZ format for volumes. using brain.finalsurfs as T1 volume... $Id: mris_make_surfaces.c,v 1.99.2.5 2008/08/21 22:48:22 nicks Exp $ $Id: mrisurf.c,v 1.557.2.15 2008/07/30 17:54:19 greve Exp $ reading volume /Volumes/DataDisk/freesurf/adrian/mri/filled.mgz... reading volume /Volumes/DataDisk/freesurf/adrian/mri/brain.finalsurfs.mgz... reading volume /Volumes/DataDisk/freesurf/adrian/mri/wm.mgz... 19879 bright wm thresholded. 4 bright non-wm voxels segmented. reading original surface position from /Volumes/DataDisk/freesurf/adrian/surf/rh.orig... computing class statistics... border white: 277588 voxels (1.65%) border gray 287750 voxels (1.72%) WM (103.0): 103.2 +- 5.6 [70.0 --> 110.0] GM (88.0) : 86.5 +- 9.1 [30.0 --> 110.0] setting MIN_GRAY_AT_WHITE_BORDER to 75.9 (was 70) setting MAX_BORDER_WHITE to 111.6 (was 105) setting MIN_BORDER_WHITE to 85.0 (was 85) setting MAX_CSF to 66.8 (was 40) setting MAX_GRAY to 100.4 (was 95) setting MAX_GRAY_AT_CSF_BORDER to 80.4 (was 75) setting MIN_GRAY_AT_CSF_BORDER to 57.7 (was 40) repositioning cortical surface to gray/white boundary smoothing T1 volume with sigma = 2.000 vertex spacing 0.82 +- 0.21 (0.02-->6.25) (max @ vno 57593 --> 140123) face area 0.28 +- 0.12 (0.00-->4.95) mean absolute distance = 0.84 +- 1.11 3662 vertices more than 2 sigmas from mean. averaging target values for 5 iterations... smoothing contralateral hemisphere... intensity peaks found at WM=106, GM=85 using class modes intead of means.... mean inside = 100.7, mean outside = 89.6 smoothing surface for 5 iterations... inhibiting deformation at non-cortical midline structures... mean border=92.7, 106 (106) missing vertices, mean dist 0.2 [0.8 (%36.9)->0.8 (%63.1))] %59 local maxima, %37 large gradients and % 0 min vals, 0 gradients ignored tol=1.0e-04, sigma=2.0, host=ALW-A, nav=4, nbrs=2, l_repulse=5.000, l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000 mom=0.00, dt=0.50 vertex spacing 0.90 +- 0.24 (0.10-->7.73) (max @ vno 57593 --> 140123) face area 0.28 +- 0.12 (0.00-->4.09) vertex spacing 0.91 +- 0.25 (0.08-->8.87) (max @ vno 57593 --> 140123) face area 0.28 +- 0.13 (0.00-->4.04) smoothing T1 volume with sigma = 1.000 vertex spacing 0.91 +- 0.25 (0.06-->8.92) (max @ vno 57593 --> 140123) face area 0.28 +- 0.13 (0.00-->4.04) mean absolute distance = 0.46 +- 0.83 3512 vertices more than 2 sigmas from mean. averaging target values for 5 iterations... 000: dt: 0.0000, sse=3631140.5, rms=6.62 001: dt: 0.5000, sse=4303983.5, rms=4.71 002: dt: 0.5000, sse=4324421.5, rms=3.47 003: dt: 0.5000, sse=4337002.0, rms=2.68 004: dt: 0.5000, sse=4291947.5, rms=2.21 005: dt: 0.5000, sse=4263108.5, rms=1.94 006: dt: 0.5000, sse=4212978.0, rms=1.80 007: dt: 0.5000, sse=4200574.0, rms=1.72 rms = 1.68, time step reduction 1 of 3 to 0.250... 008: dt: 0.5000, sse=4191339.5, rms=1.68 009: dt: 0.2500, sse=3181011.8, rms=1.44 rms = 1.42, time step reduction 2 of 3 to 0.125... 010: dt: 0.2500, sse=3087899.5, rms=1.42 rms = 1.41, time step reduction 3 of 3 to 0.062... 011: dt: 0.1250, sse=3061586.0, rms=1.41 positioning took 75.5 minutes inhibiting deformation at non-cortical midline structures... mean border=94.2, 141 (49) missing vertices, mean dist -0.2 [0.6 (%61.8)->0.3 (%38.2))] %65 local maxima, %31 large gradients and % 0 min vals, 0 gradients ignored tol=1.0e-04, sigma=1.0, host=ALW-A, nav=2, nbrs=2, l_repulse=5.000, l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000 mom=0.00, dt=0.50 vertex spacing 0.90 +- 0.24 (0.03-->9.51) (max @ vno 57593 --> 140123) face area 0.34 +- 0.16 (0.00-->5.05) smoothing T1 volume with sigma = 0.500 vertex spacing 0.89 +- 0.24 (0.07-->9.67) (max @ vno 57593 --> 140123) face area 0.34 +- 0.16 (0.00-->5.09) mean absolute distance = 0.39 +- 0.57 4028 vertices more than 2 sigmas from mean. averaging target values for 5 iterations... 000: dt: 0.0000, sse=3383843.2, rms=3.03 012: dt: 0.5000, sse=3668512.5, rms=2.02 013: dt: 0.5000, sse=3762432.5, rms=1.65 014: dt: 0.5000, sse=3746829.0, rms=1.49 015: dt: 0.5000, sse=3832901.5, rms=1.41 rms = 1.41, time step reduction 1 of 3 to 0.250... 016: dt: 0.5000, sse=3843775.0, rms=1.41 017: dt: 0.2500, sse=3401710.2, rms=1.27 rms = 1.26, time step reduction 2 of 3 to 0.125... 018: dt: 0.2500, sse=3332062.8, rms=1.26 rms = 1.26, time step reduction 3 of 3 to 0.062... 019: dt: 0.1250, sse=3308422.0, rms=1.26 positioning took 36.1 minutes inhibiting deformation at non-cortical midline structures... removing 3 vertex label from ripped group mean border=95.9, 155 (28) missing vertices, mean dist -0.2 [0.5 (%68.6)->0.2 (%31.4))] %78 local maxima, %18 large gradients and % 0 min vals, 0 gradients ignored tol=1.0e-04, sigma=0.5, host=ALW-A, nav=1, nbrs=2, l_repulse=5.000, l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000 mom=0.00, dt=0.50 vertex spacing 0.89 +- 0.24 (0.06-->9.72) (max @ vno 57593 --> 140123) face area 0.34 +- 0.16 (0.00-->5.02) Segmentation fault Darwin ALW-Apple-G5.local 8.11.0 Darwin Kernel Version 8.11.0: Wed Oct 10 18:26:00 PDT 2007; root:xnu-792.24.17~1/RELEASE_PPC Power Macintosh powerpc recon-all exited with ERRORS at Sun Jan 11 11:29:52 GMT 2009

3 5

Gray matter question
by Martin Ystad 13 Jan '09

13 Jan '09

Hi all, I have a question relating to some quite poor data I have been analyzing. It seems that not all of the gray matter is included in the segmentation, especially in the lower part of the left temporal lobes (see attached image). It looks like the white matter has been correctly segmented in the area (i have also included 3 wm-images from the slices around the problematic area). I am not sure however, whether the tissue seen outside the pial surface is in fact gray matter. I have had some problems during scull stripping on these subjects. I would appreciate any opinions and tips on this. Regards, Martin Ystad

1 0

segementation
by GaBbo Go. Es. 13 Jan '09

13 Jan '09

hello i'm asking about a the cerebellum segmentation,i'm sending someimages, wich are exacly the same slice, but in two views(coronal and sagital)in those slices y show how looks the cerebellum together with cortex, and how i separated them. Thanks Gabriel. _________________________________________________________________ Chatea sin límites en Messenger con la tarifa plana de Orange http://serviciosmoviles.es.msn.com/messenger/orange.aspx

1 0

Res: [Freesurfer] Segmentation
by Kelly Silva 13 Jan '09

13 Jan '09

Hi, Bruce I´m sending some pictures of aseg.mgz. Is this well done? Is there any objective and specific criteria to separate the cerebelum from the cortex? Is really necessary to do the manual segmentation on that area? Thanks, Kelly ________________________________ De: Bruce Fischl <fischl(a)nmr.mgh.harvard.edu> Para: Kelly Silva <kcasilva(a)yahoo.com.br> Cc: freesurfer <freesurfer(a)nmr.mgh.harvard.edu> Enviadas: Segunda-feira, 12 de Janeiro de 2009 15:40:34 Assunto: Re: [Freesurfer] Segmentation Hi Kelly, did you check the aseg.mgz? Did it separate them properly? cheers, Bruce On Mon, 12 Jan 2009, Kelly Silva wrote: > Hello, > I´m sending an image and I want to know how is the best way to separate cerebelum from the cortex with the preservation of the both structures. > Thanks! > Best regards, > Kelly > > > Veja quais são os assuntos do momento no Yahoo! +Buscados > http://br.maisbuscados.yahoo.com Veja quais são os assuntos do momento no Yahoo! +Buscados http://br.maisbuscados.yahoo.com

1 0

Cortical thickness in WM disease - experience
by Martin Kavec 13 Jan '09

13 Jan '09

Hi, I have been running quite a few clinical subjects (close to 300) through FS pipeline and comparing cortical thickness from parcellated cortex for each individual subject to its agematched controls. The subject clinical symptoms are not specific, ranging from amnesia, reduced ability to generate words, confusion, ... Every now and that I see that the cortical thickness is suspiciously higher than STD of the controls even if there are no leftovers after brain extraction (I specifically verify it, and if necessary do the corrections). In the vast majority of these cases I also find lower total white matter volume. I am speculating, if possible subcortical WM disease (as detected by reduced total volume of the WM) may come into the play. If subcortical WM gets darker, near the intensity of the GM, the cortical thickness may be overestimated. Could anybody comment on this idea? I suppose there is no way of correcting this. At the same time I wonder, whether cortical atrophy in MS assessed by the FS is accurate. The cortical atrophy reported in MS by FS methods (Sailer2003) was highly focal, and I am wondering if such atrophy can reflect the wide range of disables and clinical symptoms. I would appreciate any comments to my thought. Best, Martin

2 2

Qdec correlation analyses
by Xie, Hong 12 Jan '09

12 Jan '09

Hello, freesurfer group, I have run qdec for comparing thickness between two groups. When qdec does a correlation analyses for thickness versus a second variable: 1) Does the second variable have to be a continuous interval variable or 2) can the second variable be an ordinal variable with more than 2 levels? In the case of the correlation between two continuous variable, is the test a Pearson correlation? If 2) is possible, is the correlation a Spearman correlation? Thank for your help, Hong Xie

2 7

Reusing ROIs
by Martin Kavec 12 Jan '09

12 Jan '09

Hi, For my group analysis I am thinking of reusing a specific set of cortical ROIs from already published data. I suppose that a target template (fsaverage) and ROIs itself should be sufficient to have. If I use the same fsaverage for my cohort, I should be able to get the data out of the ROIs of my subjects, and possibly compare it to the published results. Isn't it so? Thanks in advance for clarification, Martin

1 0

retinotopy and alternating stimulus direction within-run
by Jeff Phillips 12 Jan '09

12 Jan '09

Hello all, I am wondering if the FS FAST retinotopy analysis can deal with within-run alternations of stimulus direction. I have collected data in which eccentricity and polar angle were manipulated in separate runs, but within each run, a cycle of stimulation in one direction was followed by a cycle in the opposite direction. For example, 32 s of clockwise-rotating wedges were followed by 32 s of counterclockwise wedges, etc. I realize now that this may not have been a wise choice--does FS FAST have some paradigm file option for alternating stimulation? If not, is my best solution to cut and splice my runs, dividing each into two mini-runs of single-direction stimulation? Thanks, Jeff

2 1

(no subject)
by Gabriel GLZ 12 Jan '09

12 Jan '09

hello in the case that i have a ROI and i don't know wich voxeles are in there, or the coordenates of those voxeles, i want to create a specific label that only contains those voxeles, how can i do that??' _________________________________________________________________ Arrastrar y colocar: acceso muy fácil al uso compartido de fotos con Fotos de Windows Live™. http://www.microsoft.com/windows/windowslive/photos.aspx

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