Freesurfer

freesurfer@nmr.mgh.harvard.edu

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30080 discussions

qdec -- Cannot allocate memory
by Richard Frye 14 Oct '08

14 Oct '08

I am running qdec on a Mac Pro OS X 10.5.5 with dual quad pentiums mirrored RAID and 16GB memory. I have followed the instruction for creating the qdec table, loaded the data in successfully and requested an analysis with two continuous variance. The following is the final output before it crashes because it cannot allocate memory. I have the maximum memory in my machine. What can I do? $Id: mri_glmfit.c,v 1.138.2.1 2007/09/12 15:38:19 nicks Exp $ cwd /Volumes/share/MRI_Data cmdline mri_glmfit --y /Volumes/share/MRI_Data/qdec/Untitled/y.mgh --fsgd /Volumes/share/MRI_Data/qdec/Untitled/qdec.fsgd --glmdir /Volumes/share/MRI_Data/qdec/Untitled --surf fsaverage lh --label /Volumes/share/MRI_Data/fsaverage/label/lh.cortex.label --C /Volumes/share/MRI_Data/qdec/Untitled/contrasts/Avg-Intercept-thickness.mat --C /Volumes/share/MRI_Data/qdec/Untitled/contrasts/Avg-thickness-RL-Cor.mat --C /Volumes/share/MRI_Data/qdec/Untitled/contrasts/Avg-thickness-RC-Cor.mat sysname Darwin hostname Macintosh-2.local machine i386 user stevenhecht FixVertexAreaFlag = 1 UseMaskWithSmoothing 1 OneSampleGroupMean 0 y /Volumes/share/MRI_Data/qdec/Untitled/y.mgh logyflag 0 usedti 0 FSGD /Volumes/share/MRI_Data/qdec/Untitled/qdec.fsgd labelmask /Volumes/share/MRI_Data/fsaverage/label/lh.cortex.label maskinv 0 glmdir /Volumes/share/MRI_Data/qdec/Untitled DoFFx 0 Creating output directory /Volumes/share/MRI_Data/qdec/Untitled Loading y from /Volumes/share/MRI_Data/qdec/Untitled/y.mgh Matrix condition is 131.103 Found 149955 points in label. Pruning voxels by frame. Found 149955 voxels in mask Saving mask to /Volumes/share/MRI_Data/qdec/Untitled/mask.mgh search space = 59659.8 DOF = 32 Starting fit and test 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Fit completed in 0.0612333 minutes Computing spatial AR1 on surface Residual: ar1mn=0.997008, ar1std=0.001276, gstd=6.640355, fwhm=15.636842 Writing results Avg-Intercept-thickness maxvox sig=23.8959 F=850.546 at index 105774 0 0 seed=1224021971 Avg-thickness-RL-Cor maxvox sig=3.8835 F=18.8999 at index 129111 0 0 seed=1224021971 Avg-thickness-RC-Cor maxvox sig=-3.9267 F=19.2034 at index 152642 0 0 seed=1224021971 mri_glmfit done ninputs = 3 Checking inputs nframestot = 3 Allocing output Writing to /Volumes/share/MRI_Data/qdec/Untitled/contrasts.sig.mgh Reading in average area /Volumes/share/MRI_Data/fsaverage/surf/lh.white.avg.area.mgh Reading in average area /Volumes/share/MRI_Data/fsaverage/surf/lh.pial.avg.area.mgh qdec.bin(9066,0xa049cfa0) malloc: *** mmap(size=1953464320) failed (error code=12) *** error: can't allocate region *** set a breakpoint in malloc_error_break to debug TAGskip: failed to calloc 1953461248 bytes! Cannot allocate memory Best Wishes, Richard E. Frye, M.D., Ph.D., F.A.A.P. Assistant Professor of Pediatrics and Neurology University of Texas Medical School at Houston 7000 Fannin -- UCT 2478 Houston, TX 77030 Office: 713-500-3245 e-mail: richard.frye(a)gmail.com

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recon-all : in a raw or parallel?
by asaf achiron 14 Oct '08

14 Oct '08

dear all, i would like to run freesurfer during the weekend for 2 patients. what is better, to run recon-all after recon-all or to run parallel on second terminal? thank you, Asaf

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help - Intensity Normalization2 error
by Andreas Engvig 14 Oct '08

14 Oct '08

Hi, We have previously run recon-all -all on 72 subjects using Freesurfer v. 4.01. After routine edits we reprocessed the subjects. I now want to run the scans again using the updated FS v. 4.05 using the recon-all -all command. We want to have them processed in the latest version in order to do longitudinal analyses. However, when I run the v. 4.01-processed scans again, using v.4.05 I get the following error in the normalization2 part of the autorecon2 step: #@# Intensity Normalization2 Fri Oct 10 22:10:06 CEST 2008 /work/1531087.undefined.d/2003A/mri mri_normalize -aseg aseg.mgz -mask brainmask.mgz norm.mgz brain.mgz using segmentation for initial intensity normalization reading from norm.mgz... normalizing image... removing outliers in the aseg WM... 68543 control points removed building Voronoi diagram... mriMarkUnmarkedNeighbors: all inputs must be MRI_UCHAR using MR volume brainmask.mgz to mask input volume... using wm (107) threshold 97.0 for removing exterior voxels Linux compute-3-3.local 2.6.9-67.0.15.ELsmp #1 SMP Thu May 8 10:50:20 EDT 2008 x86_64 x86_64 x86_64 GNU/Linux recon-all exited with ERRORS at Fri Oct 10 22:10:51 CEST 2008 -- The same error occurs for all subjects. The error only occurs when I run the subjects on our computing cluster. I have tried to run a couple of scans on a local machine, using the same version. Running locally, I don't get the same error. We use centOS4 64bit. Any suggestions on how to solve this? Thanks ! Best regards, Andreas Engvig -- Andreas Engvig Center for the Study of Human Cognition University of Oslo PB 1094 Blindern 0317 Oslo Cell: +47 988 58 770

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Question about mri_ca_normalize
by John Sheppard 13 Oct '08

13 Oct '08

Hey Freesurfers, Couple question about 2 FS commands: first is mri_normalize, a command used in -autorecon2 pipeline. 1) Can someone tell me exactly what flags to pass this command in order for it to be as aggressive as possible in bumping up intensities, in an attempt to end up with more expanded grey/white and pial surfaces? (I'm currently losing lateral cortex in surfaces, even with extensive manual control points.) Here's a link to the command info: http://surfer.nmr.mgh.harvard.edu/fswiki/mri_normalize Next question is about mri_ca_normalize, another command used in -autorecon2: 2) From what I gather, the way to ensure that mri_ca_normalize is being as aggressive as possible in declaring white matter is by setting the flag -p to 1.0 - Is that right? Are there any other options that could help in this regard? Link: http://surfer.nmr.mgh.harvard.edu/fswiki/mri_ca_normalize My issue is sagittally-acquired data with bad inhomogeneity - namely cortical grey matter is far lateral cortex that is not as intense as it needs to be. Normalization needs to be bumping up the intensity in these regions and instead it's still lowering the intensity, resulting in loss of cortex in pial surface. Adding control points to ensure white/grey boundary is correct tends to expand the pial surface when segmentation doesn't get enough WM, which helps me, but it's not enough. Thus I want to ensure I am maximizing the potential for WM (and indirectly, pial) surface size through these normalization commands. I'm also looking at the mri_nu_correct.mni command which was taken from MNI - haven't had much luck there but I've been messing with the iteration number (and trying removing it completely). Thanks in advance! -- John Sheppard Undergraduate Student (Class of 2010) Department of Biomedical Engineering Northwestern University Phone: (630) 957-8321 E-mail: john-sheppard(a)northwestern.edu

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recon-all with voxel sizes other than 1mm^3
by Anderson Winkler 13 Oct '08

13 Oct '08

Dear all, Is there a way to have all the results from recon-all in the native image space (in our case, 0.8x0.8x0.8mm), rather than conformed to 1mm^3? Looking at the script, I'm worried that replacing the --conform to --noconform option to mri_convert may prevent the downstream steps to work correctly. Thanks in advance, Anderson PS: I saw the recent message from João to the list and the follow up, but I think that this is a different question anyhow. PS 2: Sorry for sending twice, but I think that the previous doesn't open properly in the Pipermail page. :-)

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recon-all with voxel sizes other than 1mm^3
by relkniw 13 Oct '08

13 Oct '08

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Topology fixer
by Juergen Haenggi 13 Oct '08

13 Oct '08

Dear FS experts I am wondering why there is a special kind of topology fixing (see attachment) in one of my subjects, but not in the other subjects. Why there is a different FS output in that subject? What does it mean? Should I exclude this subject? Thanks in advance Regards Juergen XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Correcting Topology of defect 1 with euler number -49 (25 loops) computing statistics for defect 1: 6251 vertices location: [ (110,113,54) - average intensity = 81.490 ] -gray ( 76.57 , 5.83 ) -white ( 91.07 , 4.53 ) -gray ( 79.48 , 21.20 ) -white ( 93.66 , 19.34 ) -intensity (76.566490 [log = -2.789462 ]- 91.071762 [log = -2.449326 ]) -curv (k1=-0.126 (0.732) , r1 = 7.947 | k2=-0.055 (0.170), r2 = 18.080 ) -curv (k1=-0.085 (0.774) , r1 = 11.717 | k2=-0.027 (0.261), r2 = 37.280 ) max face = 11956(11956) - loop = 1 (25) - ntries = [80,4792] BEST FITNESS (o)is -24.40459 mri =0.000 curv = 2.078 unmri = 16.092 ( f=0.00 , v=0.00 , c=2.08 , q= 4.16 ) ( f=0.00 , v=0.00 , c=2.08 , q= 4.16 ) BEST FITNESS (o)is -10.38215 mri =0.000 curv = 2.418 unmri = 0.711 ( f=0.00 , v=0.00 , c=2.42 , q= 4.84 ) ( f=0.00 , v=0.00 , c=2.42 , q= 4.84 ) BEST FITNESS (o)is 2.99246 mri =0.000 curv = 2.091 unmri = -11.357 ( f=0.00 , v=0.00 , c=2.09 , q= 4.18 ) ( f=0.00 , v=0.00 , c=2.09 , q= 4.18 ) BEST FITNESS (o)is 12.59626 mri =0.000 curv = 2.126 unmri = -21.101 ( f=0.00 , v=0.00 , c=2.13 , q= 4.25 ) ( f=0.00 , v=0.00 , c=2.13 , q= 4.25 ) BEST FITNESS (o)is 19.68579 mri =0.000 curv = 2.193 unmri = -28.456 ( f=0.00 , v=0.00 , c=2.19 , q= 4.39 ) ( f=0.00 , v=0.00 , c=2.19 , q= 4.39 ) BEST FITNESS (M) is 23.11130 mri =0.000 curv = 2.090 unmri = -31.473 ( f=0.00 , v=0.00 , c=2.09 , q= 4.18 ) ( f=0.00 , v=0.00 , c=2.09 , q= 4.18 ) BEST FITNESS (o)is 81.60940 mri =0.000 curv = 2.074 unmri = -89.906 ( f=0.00 , v=0.00 , c=2.07 , q= 4.15 ) ( f=0.00 , v=0.00 , c=2.07 , q= 4.15 ) 172 patches have been generated - 82 self-intersected max face = 11956(12012) - loop = 2 (25) - ntries = [80,4792] BEST FITNESS (o)is 83.25315 mri =0.000 curv = 2.202 unmri = -92.061 ( f=0.00 , v=0.00 , c=2.20 , q= 4.40 ) ( f=0.00 , v=0.00 , c=2.20 , q= 4.40 ) BEST FITNESS (M) is 89.13771 mri =0.000 curv = 2.128 unmri = -97.649 ( f=0.00 , v=0.00 , c=2.13 , q= 4.26 ) ( f=0.00 , v=0.00 , c=2.13 , q= 4.26 ) BEST FITNESS (o)is 92.49757 mri =0.000 curv = 2.120 unmri = -100.978 ( f=0.00 , v=0.00 , c=2.12 , q= 4.24 ) ( f=0.00 , v=0.00 , c=2.12 , q= 4.24 ) BEST FITNESS (M) is 113.05239 mri =0.000 curv = 2.076 unmri = -121.356 ( f=0.00 , v=0.00 , c=2.08 , q= 4.15 ) ( f=0.00 , v=0.00 , c=2.08 , q= 4.15 ) BEST FITNESS (o)is 226.29410 mri =0.000 curv = 2.074 unmri = -234.589 ( f=0.00 , v=0.00 , c=2.07 , q= 4.15 ) ( f=0.00 , v=0.00 , c=2.07 , q= 4.15 ) 184 patches have been generated - 104 self-intersected max face = 11956(12100) - loop = 3 (25) - ntries = [80,4792] BEST FITNESS (o)is 227.95853 mri =0.000 curv = 2.197 unmri = -236.746 ( f=0.00 , v=0.00 , c=2.20 , q= 4.39 ) ( f=0.00 , v=0.00 , c=2.20 , q= 4.39 ) BEST FITNESS (M) is 257.73714 mri =0.000 curv = 2.076 unmri = -266.039 ( f=0.00 , v=0.00 , c=2.08 , q= 4.15 ) ( f=0.00 , v=0.00 , c=2.08 , q= 4.15 ) BEST FITNESS (M) is 266.92345 mri =0.000 curv = 2.239 unmri = -275.878 ( f=0.00 , v=0.00 , c=2.24 , q= 4.48 ) ( f=0.00 , v=0.00 , c=2.24 , q= 4.48 ) 171 patches have been generated - 82 self-intersected max face = 11956(12156) - loop = 4 (25) - ntries = [80,4792] BEST FITNESS (o)is 255.25060 mri =0.000 curv = 2.501 unmri = -265.254 ( f=0.00 , v=0.00 , c=2.50 , q= 5.00 ) ( f=0.00 , v=0.00 , c=2.50 , q= 5.00 ) BEST FITNESS (o)is 268.93239 mri =0.000 curv = 2.314 unmri = -278.189 ( f=0.00 , v=0.00 , c=2.31 , q= 4.63 ) ( f=0.00 , v=0.00 , c=2.31 , q= 4.63 ) BEST FITNESS (o)is 278.25330 mri =0.000 curv = 2.245 unmri = -287.235 ( f=0.00 , v=0.00 , c=2.25 , q= 4.49 ) ( f=0.00 , v=0.00 , c=2.25 , q= 4.49 ) BEST FITNESS (o)is 278.43976 mri =0.000 curv = 2.769 unmri = -289.517 ( f=0.00 , v=0.00 , c=2.77 , q= 5.54 ) ( f=0.00 , v=0.00 , c=2.77 , q= 5.54 ) BEST FITNESS (o)is 301.51737 mri =0.000 curv = 4.565 unmri = -319.779 ( f=0.00 , v=0.00 , c=4.57 , q= 9.13 ) ( f=0.00 , v=0.00 , c=4.57 , q= 9.13 ) BEST FITNESS (o)is 303.06038 mri =0.000 curv = 2.404 unmri = -312.676 ( f=0.00 , v=0.00 , c=2.40 , q= 4.81 ) ( f=0.00 , v=0.00 , c=2.40 , q= 4.81 ) 179 patches have been generated - 93 self-intersected max face = 11956(12228) - loop = 5 (25) - ntries = [80,4792] BEST FITNESS (o)is 302.83623 mri =0.000 curv = 2.582 unmri = -313.164 ( f=0.00 , v=0.00 , c=2.58 , q= 5.16 ) ( f=0.00 , v=0.00 , c=2.58 , q= 5.16 ) BEST FITNESS (o)is 308.96110 mri =0.000 curv = 2.599 unmri = -319.358 ( f=0.00 , v=0.00 , c=2.60 , q= 5.20 ) ( f=0.00 , v=0.00 , c=2.60 , q= 5.20 ) BEST FITNESS (o)is 309.47138 mri =0.000 curv = 2.400 unmri = -319.073 ( f=0.00 , v=0.00 , c=2.40 , q= 4.80 ) ( f=0.00 , v=0.00 , c=2.40 , q= 4.80 ) BEST FITNESS (o)is 314.86781 mri =0.000 curv = 2.408 unmri = -324.500 ( f=0.00 , v=0.00 , c=2.41 , q= 4.82 ) ( f=0.00 , v=0.00 , c=2.41 , q= 4.82 ) BEST FITNESS (M) is 351.95513 mri =0.000 curv = 2.514 unmri = -362.010 ( f=0.00 , v=0.00 , c=2.51 , q= 5.03 ) ( f=0.00 , v=0.00 , c=2.51 , q= 5.03 ) 176 patches have been generated - 91 self-intersected max face = 11956(12312) - loop = 6 (25) - ntries = [80,4792] BEST FITNESS (o)is 353.55714 mri =0.000 curv = 2.640 unmri = -364.117 ( f=0.00 , v=0.00 , c=2.64 , q= 5.28 ) ( f=0.00 , v=0.00 , c=2.64 , q= 5.28 ) BEST FITNESS (M) is 359.49714 mri =0.000 curv = 2.564 unmri = -369.753 ( f=0.00 , v=0.00 , c=2.56 , q= 5.13 ) ( f=0.00 , v=0.00 , c=2.56 , q= 5.13 ) BEST FITNESS (M) is 362.60800 mri =0.000 curv = 2.758 unmri = -373.641 ( f=0.00 , v=0.00 , c=2.76 , q= 5.52 ) ( f=0.00 , v=0.00 , c=2.76 , q= 5.52 ) BEST FITNESS (o)is 363.29253 mri =0.000 curv = 2.518 unmri = -373.366 ( f=0.00 , v=0.00 , c=2.52 , q= 5.04 ) ( f=0.00 , v=0.00 , c=2.52 , q= 5.04 ) BEST FITNESS (o)is 377.19295 mri =0.000 curv = 2.597 unmri = -387.583 ( f=0.00 , v=0.00 , c=2.60 , q= 5.19 ) ( f=0.00 , v=0.00 , c=2.60 , q= 5.19 ) BEST FITNESS (o)is 395.29546 mri =0.000 curv = 2.470 unmri = -405.177 ( f=0.00 , v=0.00 , c=2.47 , q= 4.94 ) ( f=0.00 , v=0.00 , c=2.47 , q= 4.94 ) 172 patches have been generated - 89 self-intersected max face = 11956(12464) - loop = 7 (25) - ntries = [80,4792] BEST FITNESS (o)is -11.45876 mri =0.000 curv = 2.481 unmri = 1.536 ( f=0.00 , v=0.00 , c=2.48 , q= 4.96 ) ( f=0.00 , v=0.00 , c=2.48 , q= 4.96 ) BEST FITNESS (o)is 406.63200 mri =0.000 curv = 2.475 unmri = -416.534 ( f=0.00 , v=0.00 , c=2.48 , q= 4.95 ) ( f=0.00 , v=0.00 , c=2.48 , q= 4.95 ) BEST FITNESS (o)is 558.18150 mri =0.000 curv = 2.897 unmri = -569.768 ( f=0.00 , v=0.00 , c=2.90 , q= 5.79 ) ( f=0.00 , v=0.00 , c=2.90 , q= 5.79 ) BEST FITNESS (o)is 566.08901 mri =0.000 curv = 2.601 unmri = -576.491 ( f=0.00 , v=0.00 , c=2.60 , q= 5.20 ) ( f=0.00 , v=0.00 , c=2.60 , q= 5.20 ) 179 patches have been generated - 101 self-intersected max face = 11956(12568) - loop = 8 (25) - ntries = [80,4792] BEST FITNESS (o)is 567.67052 mri =0.000 curv = 2.732 unmri = -578.597 ( f=0.00 , v=0.00 , c=2.73 , q= 5.46 ) ( f=0.00 , v=0.00 , c=2.73 , q= 5.46 ) BEST FITNESS (M) is 570.77103 mri =0.000 curv = 2.674 unmri = -581.468 ( f=0.00 , v=0.00 , c=2.67 , q= 5.35 ) ( f=0.00 , v=0.00 , c=2.67 , q= 5.35 ) BEST FITNESS (o)is 585.13960 mri =0.000 curv = 2.618 unmri = -595.614 ( f=0.00 , v=0.00 , c=2.62 , q= 5.24 ) ( f=0.00 , v=0.00 , c=2.62 , q= 5.24 ) BEST FITNESS (M) is 613.60922 mri =0.000 curv = 2.894 unmri = -625.184 ( f=0.00 , v=0.00 , c=2.89 , q= 5.79 ) ( f=0.00 , v=0.00 , c=2.89 , q= 5.79 ) 189 patches have been generated - 101 self-intersected max face = 11956(12724) - loop = 9 (25) - ntries = [80,4792] BEST FITNESS (o)is 612.35975 mri =0.000 curv = 2.881 unmri = -623.884 ( f=0.00 , v=0.00 , c=2.88 , q= 5.76 ) ( f=0.00 , v=0.00 , c=2.88 , q= 5.76 ) BEST FITNESS (M) is 624.30301 mri =0.000 curv = 3.128 unmri = -636.815 ( f=0.00 , v=0.00 , c=3.13 , q= 6.26 ) ( f=0.00 , v=0.00 , c=3.13 , q= 6.26 ) BEST FITNESS (o)is 627.32114 mri =0.000 curv = 2.855 unmri = -638.742 ( f=0.00 , v=0.00 , c=2.86 , q= 5.71 ) ( f=0.00 , v=0.00 , c=2.86 , q= 5.71 ) BEST FITNESS (M) is 633.64074 mri =0.000 curv = 2.894 unmri = -645.218 ( f=0.00 , v=0.00 , c=2.89 , q= 5.79 ) ( f=0.00 , v=0.00 , c=2.89 , q= 5.79 ) 183 patches have been generated - 106 self-intersected max face = 11956(12856) - loop = 10 (25) - ntries = [80,4792] BEST FITNESS (o)is 635.23923 mri =0.000 curv = 3.021 unmri = -647.324 ( f=0.00 , v=0.00 , c=3.02 , q= 6.04 ) ( f=0.00 , v=0.00 , c=3.02 , q= 6.04 ) BEST FITNESS (o)is 635.68132 mri =0.000 curv = 2.962 unmri = -647.529 ( f=0.00 , v=0.00 , c=2.96 , q= 5.92 ) ( f=0.00 , v=0.00 , c=2.96 , q= 5.92 ) BEST FITNESS (M) is 637.63714 mri =0.000 curv = 2.886 unmri = -649.179 ( f=0.00 , v=0.00 , c=2.89 , q= 5.77 ) ( f=0.00 , v=0.00 , c=2.89 , q= 5.77 ) BEST FITNESS (M) is 644.34499 mri =0.000 curv = 3.126 unmri = -656.849 ( f=0.00 , v=0.00 , c=3.13 , q= 6.25 ) ( f=0.00 , v=0.00 , c=3.13 , q= 6.25 ) 183 patches have been generated - 101 self-intersected max face = 11956(12904) - loop = 11 (25) - ntries = [80,4792] BEST FITNESS (o)is 645.98106 mri =0.000 curv = 3.244 unmri = -658.957 ( f=0.00 , v=0.00 , c=3.24 , q= 6.49 ) ( f=0.00 , v=0.00 , c=3.24 , q= 6.49 ) BEST FITNESS (o)is 651.50315 mri =0.000 curv = 3.191 unmri = -664.268 ( f=0.00 , v=0.00 , c=3.19 , q= 6.38 ) ( f=0.00 , v=0.00 , c=3.19 , q= 6.38 ) BEST FITNESS (M) is 653.40081 mri =0.000 curv = 3.334 unmri = -666.736 ( f=0.00 , v=0.00 , c=3.33 , q= 6.67 ) ( f=0.00 , v=0.00 , c=3.33 , q= 6.67 ) BEST FITNESS (M) is 653.59195 mri =0.000 curv = 3.286 unmri = -666.738 ( f=0.00 , v=0.00 , c=3.29 , q= 6.57 ) ( f=0.00 , v=0.00 , c=3.29 , q= 6.57 ) 186 patches have been generated - 101 self-intersected max face = 11956(12956) - loop = 12 (25) - ntries = [80,4792] BEST FITNESS (o)is 655.23246 mri =0.000 curv = 3.403 unmri = -668.845 ( f=0.00 , v=0.00 , c=3.40 , q= 6.81 ) ( f=0.00 , v=0.00 , c=3.40 , q= 6.81 ) BEST FITNESS (o)is 656.24508 mri =0.000 curv = 3.498 unmri = -670.236 ( f=0.00 , v=0.00 , c=3.50 , q= 7.00 ) ( f=0.00 , v=0.00 , c=3.50 , q= 7.00 ) BEST FITNESS (o)is 665.92804 mri =0.000 curv = 3.232 unmri = -678.857 ( f=0.00 , v=0.00 , c=3.23 , q= 6.46 ) ( f=0.00 , v=0.00 , c=3.23 , q= 6.46 ) BEST FITNESS (M) is 678.57554 mri =0.000 curv = 3.290 unmri = -691.737 ( f=0.00 , v=0.00 , c=3.29 , q= 6.58 ) ( f=0.00 , v=0.00 , c=3.29 , q= 6.58 ) ----------------------------------------------------------- Juergen Haenggi Ph.D. (Dr. des.) Division of Neuropsychology Institute of Psychology University of Zurich Binzmuehlestrasse 14, PO Box 25 8050 Zurich, Switzerland 0041 44 635 73 97 (phone office) 0041 76 445 86 84 (phone mobile) 0041 44 635 74 09 (fax office) BIN 4.D.04 (office room number) j.haenggi(a)psychologie.uzh.ch (email) http://www.psychologie.uzh.ch/neuropsy/ (website) http://www.juergenhaenggi.ch (private website) -----------------------------------------------------------

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Creating template rat model
by Mark Bouts 13 Oct '08

13 Oct '08

Hi, I'm trying to create a template model for rats. I've learned through the surface registration template (http://surfer.nmr.mgh.harvard.edu/fswiki/SurfaceRegAndTemplates) that I have to run the recon-all procedure at least once. However when I run the recon-all -autorecon1 option it stops at the the talairach detection after completing the talairach_avi. With the message: Talairach Failure Detection ERROR: talairach_afd: Talairach Transform: transforms/talairach.xfm ***FAILED*** (p=0.0000, pval=0.0000 < threshold=0.0050) I read through different messages on the mailing list that I had to check the nu.mgz file with tkmedit. This file looks ok considering the fact that a rat brain is considerably smaller. So my question I like to ask is: how to continue? What could I try? Is there a template available or does anyone have experience with creating a template for a rat? Thanks! Mark

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Re: Freesurfer Digest, Vol 56, Issue 20
by Sebastian Moeller 13 Oct '08

13 Oct '08

Hi All, On Oct 11, 2008, at 11:23 PM, freesurfer-request(a)nmr.mgh.harvard.edu wrote: > Message: 4 > Date: Sat, 11 Oct 2008 15:54:05 -0500 > From: "Richard Frye" <richard.frye(a)gmail.com> > Subject: [Freesurfer] qdec -- Cannot allocate memory > To: freesurfer(a)nmr.mgh.harvard.edu > Message-ID: > <2b8a4fa00810111354x24e43212ob7f3e164426c38c8(a)mail.gmail.com> > Content-Type: text/plain; charset="iso-8859-1" > > I am running qdec on a Mac Pro OS X 10.5.5 with dual quad pentiums > mirrored > RAID and 16GB memory. That does not help, current (I hope) freesurfer is compiled for 32 bit on MacOSX. So the 16GB can not be seen by qdec, it has to work with maximally 4GB, most likely 2GB or 3GB. To test the bitness of any program (replace /opt/freesurfer/bin/qdec.bin with the name of the executable you are going to test) run the following in a terminal window: "file /opt/freesurfer/bin/qdec.bin" the result will be: qdec.bin: Mach-O executable i386 i386 means 32bit intel, otherwise you would get: Mach-O 64-bit executable x86_64 x86_64 is the label for 64 bit intel. You need a true 64-bit built to be able to use more memory. The Linux 64bit versions can do just that. ahoi good luck Sebastian > > > I have followed the instruction for creating the qdec table, loaded > the data > in successfully and requested an analysis with two continuous > variance. The > following is the final output before it crashes because it cannot > allocate > memory. I have the maximum memory in my machine. What can I do? -- Sebastian Moeller Tel.: 04 21 - 2 18 - 90 96 Fax.: 04 21 - 2 18 - 90 04 GSM: 0 15 77 - 1 90 31 41 moeller(a)neuro.uni-bremen.de AG Kreiter / FB 2 Institut fuer Hirnforschung III Abteilung Theoretische Neurobiologie Universitaet Bremen Biogarten Hochschulring 16a Postfach 33 04 40 28359 Bremen

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FSPGR axial 3D WITH a slcie thickness of 2.6
by asaf achiron 12 Oct '08

12 Oct '08

Dear group, in 2009 we will change our MRI protocol. we are doing on a GE scanner 3T, T1-FSPGR axial slcies, 3D with a slice thickness of 2.6 and overlay of 50%. will it be possible to work with this data on FreeSurfer? thank you, asaf

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