Freesurfer March 2014

freesurfer@nmr.mgh.harvard.edu

147 participants
247 discussions

Pial surface area
by Anita van Loenhoud 21 Mar '14

21 Mar '14

Hi mailinglist, I want to obtain aparc.stats for pial instead of white matter surface area. I read that I therefore should adjust mris_anatomical_stats. However, when I run this command separately, the following error occurs: cannot allocate memory Then I tried to put autorecon3 -parcstats in front in this command, but now it says: Flag mris_anatomical_stats unrecognized. Any help would be greatly appreciated, Anita

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LME advice
by Eric Cunningham 20 Mar '14

20 Mar '14

Hello Freesurfer experts, I am getting some unusual results with the lme pipeline, and I would appreciate help with identifying the most likely step in which the problem may have originated. Running lme_fit_FS.m on a single vertex, followed by lme_F on the output of that (stats) yields a p-value of 0. This is because the fcdf function in matlab rounds to 1 if the F-value is big enough (in our case it rounds at about 80, and our F-value is 123). This being the case, we are trying to determine whether this is (1) a problem with the data, (2) a problem with the script somewhere, or (3) a system setting I don't know about. I'm not sure if you have enough information, but can you tell me if the F-values and Beta values look possible (reasonable?)? Thanks for any advice you can provide. -E Starting Fisher scoring iterations Likelihood at FS iteration 1 : 484.5267 Gradient norm: 53.7987 Likelihood at FS iteration 2 : 484.5984 Gradient norm: 1.3858 Likelihood at FS iteration 3 : 484.5985 Gradient norm: 0.022222 Likelihood at FS iteration 4 : 484.5985 Gradient norm: 0.00056884 Total elapsed time is 0.24038 seconds stats = Bhat: [7x1 double] CovBhat: [7x7 double] bihat: [1x93 double] Covbihat: [93x1 double] phisqhat: 0.0110 SIGMA: [345x5 double] W: [345x5 double] Dhat: 0.0213 X: [345x7 double] Zcols: 1 re: [345x1 double] ni: [93x1 double] lreml: 484.5985 st = 1 K>> stats.Bhat ans = 3.1531 -0.0559 0.0148 -0.0154 -0.0309 -0.0767 -0.0229 K>> -0.0559 K>> fstats = lme_F(stats,contrastmatrix) fstats = F: 123.4649 pval: 0 sgn: -1 df: [1 284.0811]

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Overinclusion of brain volume during segmentation - Question
by Christina Chen 20 Mar '14

20 Mar '14

Hi! If the cortical surface outlines are fine, but there is an overinclusion of brain volume during segmentation, how should I fix this? Can we calculate brain volume based on the cortical surface outlines -- if so, how? Thanks! Christina

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Recon process
by Lin, Amy (NIH/NIMH) [F] 20 Mar '14

20 Mar '14

Hello all, I think this is a fairly simple question, but I could not find an existing answer online. If I close out the terminal window while recon is running, will the process end? I've had the issue in the past where my computer has gone to sleep and the process ends up exiting with error. Also, is it possible to rerun a recon command after a previous failed attempt without being prompted to delete the older files that had already been made? I know that usually if you attempt to rerun a recon command after you have already tried, you're usually prompted to remove the older files. This time around, I wasn't ever prompted to do that but the scripts show that the last time recon-all ran, it completed without error. Thanks very much!

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Sample bert information
by Saurabh Thakur 20 Mar '14

20 Mar '14

Hello Freesurfer Expert, Can you share the freesurfer sample named *bert* information such as age,M/F and other details. Thanks in advance, cheers Saurabh Thakur,

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Extracting Mean Diffusivity values
by Rotem Saar 20 Mar '14

20 Mar '14

Dear Doug, I'm now working with freesurfer 5.3, for this example, subject is "Anatomy0981". A while ago I wrote to the list trying to extract the MD values for each ROI as in the diffusion analysis that ends with the FA value for each ROI (for each subject). I wrote my FA script, and asked u to advise on how to convert it to my needs (MD instead of FA), u wrote - > Use mri_label2vol to transfer the wmparc.mgz into the DTI space, then > use mri_segstats with --seg-erode 1 to compute summaries of the MD in > each region (steps below for FA values ended fine) - this is what I did - 1) dt_recon --i /usr/local/freesurfer/ subjects/Anatomy0981/DTI/I160.dcm --s Anatomy0981 --o /usr/local/freesurfer/subjects/FOLDER-NAME/DTI --b /usr/local/freesurfer/subjects/Anatomy0981/DTI/bvals.bval /usr/local/freesurfer/subjects/Anatomy0981/DTI/bvecs.bvec 2) mri_vol2vol --mov /usr/local/freesurfer/subjects/Anatomy0981/DTI/lowb.nii \ --targ /usr/local/freesurfer/subjects/Anatomy0981/mri/wmparc.mgz \ --inv --interp nearest --o /usr/local/freesurfer/subjects/Anatomy0981/mri/wmparc2diff.mgz \ --reg /usr/local/freesurfer/subjects/Anatomy0981/DTI/register.dat --no-save-reg 3) mri_label2vol --mov /usr/local/freesurfer/subjects/Anatomy0981/DTI/lowb.nii \ --targ /usr/local/freesurfer/subjects/Anatomy0981/mri/aparc+aseg.mgz \ --inv --interp nearest --o /usr/local/freesurfer/subjects/Anatomy0981/mri/aparc+aseg2diff.mgz \ --reg /usr/local/freesurfer/subjects/Anatomy0981/DTI/register.dat --no-save-reg 4) mri_segstats --seg-erode 1 /usr/local/freesurfer/subjects/Anatomy0981/mri/wmparc2diff.mgz --ctab $FREESURFER_HOME/FreeSurferColorLUT.txt --i /usr/local/freesurfer/subjects/Anatomy0981/DTI/fa-masked.mgz --sum /usr/local/freesurfer/subjects/Anatomy0981/stats/all_stats_MD-masked error after step 3: ERROR: Option --mov unknown Trying to use vol2vol instead of label2vol ended successfully, but then when trying to perform step 4, it failed again - ERROR: Option /usr/local/freesurfer/subjects/Anatomy0981/mri/wmparc2diff.mgz unknown Can u advise on what am I doing wrong ? Thanks !! Rotem Saar-Ashkenazy Department of Brain and Cognitive Science Ben Gurion University of the Negev Beer-Sheva 84105 Israel

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brain.mgz image error
by Saurabh Thakur 20 Mar '14

20 Mar '14

Hello Freesurfer expert , I am sending you the image of brain.mgz screen-shot. Is the area highlighted is part of cortex or it is due to skull stripping error. Please clarify. Thanks in advance, cheers Saurabh Thakur,

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expert options command
by Michael Green 20 Mar '14

20 Mar '14

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what is inflating to sphere rms error?
by chenchunhuichina 20 Mar '14

20 Mar '14

Dear Freesurfers, I am new to freesurfer and I am afraid of doing something wrong, so I am writing to ask is this error indicating something wrong with my data? Any help is appreciated. below are detials of my question. Thank you! I used freesurfer-Linux-centos4_x86_64-stable-pub-v5.3.0 with this command fsl_sub -N cch recon-all -i ${i} -s FSsub${i:3:5} -all I checked the O file from fsl_sub and it said at the end "recon-all -s FSsub12534 finished without error at Thu Jan 23 15:44:35 CST 2014 done" Seems it's OK then checked the e file from fsl_sub (standard_in) 2: Error: comparison in expression Seems this is a problem of fsl_sub, According to https://mail.nmr.mgh.harvard.edu/pipermail/freesurfer/2012-May/023961.html I guess I can ignore it? Then I checked the recon-all.log file and find a lot of "error", Someone asked this question and got the answer "We see this mysterious message sometimes...usually things are fine". So when and why get there errors and does they always fine? https://mail.nmr.mgh.harvard.edu/pipermail/freesurfer/2011-October/020810.h… the "rms radial error" and "distance error " are below . $ grep -n error FSsub12534/scripts/recon-all.log 2931:inflating to sphere (rms error < 2.00) 2932:000: dt: 0.0000, rms radial error=176.789, avgs=0 2933:005/300: dt: 0.9000, rms radial error=176.532, avgs=0 2934:010/300: dt: 0.9000, rms radial error=175.978, avgs=0 2935:015/300: dt: 0.9000, rms radial error=175.253, avgs=0 2936:020/300: dt: 0.9000, rms radial error=174.426, avgs=0 2937:025/300: dt: 0.9000, rms radial error=173.543, avgs=0 2938:030/300: dt: 0.9000, rms radial error=172.627, avgs=0 2939:035/300: dt: 0.9000, rms radial error=171.693, avgs=0 2940:040/300: dt: 0.9000, rms radial error=170.750, avgs=0 2941:045/300: dt: 0.9000, rms radial error=169.806, avgs=0 2942:050/300: dt: 0.9000, rms radial error=168.861, avgs=0 2943:055/300: dt: 0.9000, rms radial error=167.919, avgs=0 2944:060/300: dt: 0.9000, rms radial error=166.980, avgs=0 2945:065/300: dt: 0.9000, rms radial error=166.045, avgs=0 2946:070/300: dt: 0.9000, rms radial error=165.114, avgs=0 2947:075/300: dt: 0.9000, rms radial error=164.188, avgs=0 2948:080/300: dt: 0.9000, rms radial error=163.267, avgs=0 2949:085/300: dt: 0.9000, rms radial error=162.351, avgs=0 2950:090/300: dt: 0.9000, rms radial error=161.439, avgs=0 2951:095/300: dt: 0.9000, rms radial error=160.532, avgs=0 2952:100/300: dt: 0.9000, rms radial error=159.629, avgs=0 2953:105/300: dt: 0.9000, rms radial error=158.732, avgs=0 2954:110/300: dt: 0.9000, rms radial error=157.839, avgs=0 2955:115/300: dt: 0.9000, rms radial error=156.951, avgs=0 2956:120/300: dt: 0.9000, rms radial error=156.068, avgs=0 2957:125/300: dt: 0.9000, rms radial error=155.189, avgs=0 2958:130/300: dt: 0.9000, rms radial error=154.316, avgs=0 2959:135/300: dt: 0.9000, rms radial error=153.447, avgs=0 2960:140/300: dt: 0.9000, rms radial error=152.583, avgs=0 2961:145/300: dt: 0.9000, rms radial error=151.723, avgs=0 2962:150/300: dt: 0.9000, rms radial error=150.868, avgs=0 2963:155/300: dt: 0.9000, rms radial error=150.018, avgs=0 2964:160/300: dt: 0.9000, rms radial error=149.173, avgs=0 2965:165/300: dt: 0.9000, rms radial error=148.332, avgs=0 2966:170/300: dt: 0.9000, rms radial error=147.496, avgs=0 2967:175/300: dt: 0.9000, rms radial error=146.665, avgs=0 2968:180/300: dt: 0.9000, rms radial error=145.838, avgs=0 2969:185/300: dt: 0.9000, rms radial error=145.015, avgs=0 2970:190/300: dt: 0.9000, rms radial error=144.198, avgs=0 2971:195/300: dt: 0.9000, rms radial error=143.384, avgs=0 2972:200/300: dt: 0.9000, rms radial error=142.576, avgs=0 2973:205/300: dt: 0.9000, rms radial error=141.771, avgs=0 2974:210/300: dt: 0.9000, rms radial error=140.971, avgs=0 2975:215/300: dt: 0.9000, rms radial error=140.176, avgs=0 2976:220/300: dt: 0.9000, rms radial error=139.385, avgs=0 2977:225/300: dt: 0.9000, rms radial error=138.598, avgs=0 2978:230/300: dt: 0.9000, rms radial error=137.816, avgs=0 2979:235/300: dt: 0.9000, rms radial error=137.039, avgs=0 2980:240/300: dt: 0.9000, rms radial error=136.265, avgs=0 2981:245/300: dt: 0.9000, rms radial error=135.496, avgs=0 2982:250/300: dt: 0.9000, rms radial error=134.731, avgs=0 2983:255/300: dt: 0.9000, rms radial error=133.971, avgs=0 2984:260/300: dt: 0.9000, rms radial error=133.215, avgs=0 2985:265/300: dt: 0.9000, rms radial error=132.463, avgs=0 2986:270/300: dt: 0.9000, rms radial error=131.715, avgs=0 2987:275/300: dt: 0.9000, rms radial error=130.972, avgs=0 2988:280/300: dt: 0.9000, rms radial error=130.232, avgs=0 2989:285/300: dt: 0.9000, rms radial error=129.497, avgs=0 2990:290/300: dt: 0.9000, rms radial error=128.766, avgs=0 2991:295/300: dt: 0.9000, rms radial error=128.039, avgs=0 2992:300/300: dt: 0.9000, rms radial error=127.316, avgs=0 3017:distance error %100000.00 3572:pass 1: epoch 1 of 3 starting distance error %19.12 3573:pass 1: epoch 2 of 3 starting distance error %19.11 3575:starting distance error %19.02 3577:final distance error %19.05 4618:inflating to sphere (rms error < 2.00) 4619:000: dt: 0.0000, rms radial error=176.609, avgs=0 4620:005/300: dt: 0.9000, rms radial error=176.351, avgs=0 4621:010/300: dt: 0.9000, rms radial error=175.799, avgs=0 4622:015/300: dt: 0.9000, rms radial error=175.074, avgs=0 4623:020/300: dt: 0.9000, rms radial error=174.248, avgs=0 4624:025/300: dt: 0.9000, rms radial error=173.365, avgs=0 4625:030/300: dt: 0.9000, rms radial error=172.450, avgs=0 4626:035/300: dt: 0.9000, rms radial error=171.518, avgs=0 4627:040/300: dt: 0.9000, rms radial error=170.578, avgs=0 4628:045/300: dt: 0.9000, rms radial error=169.635, avgs=0 4629:050/300: dt: 0.9000, rms radial error=168.695, avgs=0 4630:055/300: dt: 0.9000, rms radial error=167.757, avgs=0 4631:060/300: dt: 0.9000, rms radial error=166.822, avgs=0 4632:065/300: dt: 0.9000, rms radial error=165.892, avgs=0 4633:070/300: dt: 0.9000, rms radial error=164.966, avgs=0 4634:075/300: dt: 0.9000, rms radial error=164.044, avgs=0 4635:080/300: dt: 0.9000, rms radial error=163.127, avgs=0 4636:085/300: dt: 0.9000, rms radial error=162.215, avgs=0 4637:090/300: dt: 0.9000, rms radial error=161.307, avgs=0 4638:095/300: dt: 0.9000, rms radial error=160.405, avgs=0 4639:100/300: dt: 0.9000, rms radial error=159.507, avgs=0 4640:105/300: dt: 0.9000, rms radial error=158.613, avgs=0 4641:110/300: dt: 0.9000, rms radial error=157.725, avgs=0 4642:115/300: dt: 0.9000, rms radial error=156.841, avgs=0 4643:120/300: dt: 0.9000, rms radial error=155.961, avgs=0 4644:125/300: dt: 0.9000, rms radial error=155.086, avgs=0 4645:130/300: dt: 0.9000, rms radial error=154.217, avgs=0 4646:135/300: dt: 0.9000, rms radial error=153.351, avgs=0 4647:140/300: dt: 0.9000, rms radial error=152.490, avgs=0 4648:145/300: dt: 0.9000, rms radial error=151.634, avgs=0 4649:150/300: dt: 0.9000, rms radial error=150.783, avgs=0 4650:155/300: dt: 0.9000, rms radial error=149.936, avgs=0 4651:160/300: dt: 0.9000, rms radial error=149.094, avgs=0 4652:165/300: dt: 0.9000, rms radial error=148.256, avgs=0 4653:170/300: dt: 0.9000, rms radial error=147.423, avgs=0 4654:175/300: dt: 0.9000, rms radial error=146.594, avgs=0 4655:180/300: dt: 0.9000, rms radial error=145.770, avgs=0 4656:185/300: dt: 0.9000, rms radial error=144.950, avgs=0 4657:190/300: dt: 0.9000, rms radial error=144.135, avgs=0 4658:195/300: dt: 0.9000, rms radial error=143.324, avgs=0 4659:200/300: dt: 0.9000, rms radial error=142.517, avgs=0 4660:205/300: dt: 0.9000, rms radial error=141.715, avgs=0 4661:210/300: dt: 0.9000, rms radial error=140.918, avgs=0 4662:215/300: dt: 0.9000, rms radial error=140.125, avgs=0 4663:220/300: dt: 0.9000, rms radial error=139.336, avgs=0 4664:225/300: dt: 0.9000, rms radial error=138.552, avgs=0 4665:230/300: dt: 0.9000, rms radial error=137.771, avgs=0 4666:235/300: dt: 0.9000, rms radial error=136.995, avgs=0 4667:240/300: dt: 0.9000, rms radial error=136.223, avgs=0 4668:245/300: dt: 0.9000, rms radial error=135.455, avgs=0 4669:250/300: dt: 0.9000, rms radial error=134.692, avgs=0 4670:255/300: dt: 0.9000, rms radial error=133.933, avgs=0 4671:260/300: dt: 0.9000, rms radial error=133.178, avgs=0 4672:265/300: dt: 0.9000, rms radial error=132.427, avgs=0 4673:270/300: dt: 0.9000, rms radial error=131.680, avgs=0 4674:275/300: dt: 0.9000, rms radial error=130.938, avgs=0 4675:280/300: dt: 0.9000, rms radial error=130.200, avgs=0 4676:285/300: dt: 0.9000, rms radial error=129.466, avgs=0 4677:290/300: dt: 0.9000, rms radial error=128.736, avgs=0 4678:295/300: dt: 0.9000, rms radial error=128.011, avgs=0 4679:300/300: dt: 0.9000, rms radial error=127.289, avgs=0 4704:distance error %100000.00 5218:pass 1: epoch 1 of 3 starting distance error %19.52 5219:pass 1: epoch 2 of 3 starting distance error %19.45 5221:starting distance error %19.40 5223:final distance error %19.42 9439:recon-all -s FSsub12534 finished without error at Thu Jan 23 15:44:35 CST 2014 2014-03-19 Chunhui Chen _________________ State Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University Beijing, China 100875

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Research Coordinator Job: Northwestern Univ. Alzheimer's Disease Center (Chicago, IL)
by Emily Rogalski 20 Mar '14

20 Mar '14

Research Coordinator job available at Northwestern University's Cognitive Neurology and Alzheimer's Disease Center in Chicago, IL. The research assistant will be responsible for analysis of neuroimaging datasets, in order to contribute to neuroscientific studies of normal aging and pathological aging. Duties include coordinating PET and MRI scans, and analyzing the resultant structural and functional imaging data. Additional duties include working on graphics for manuscripts and grants or other general lab responsibilities. Candidates must have proficiency with computer programming, ideally with relevant technical languages such as MATLAB or Python. They must be willing to learn new MRI analysis software and troubleshoot problems independently. Prior experience with neuroimaging analysis suites such as Freesurfer, FSL, or SPM would be extremely useful. Relevant backgrounds would be in Neuroscience, Biology, Psychology, Computer Science, Mathematics, and Biomedical Engineering. Openings are expected as early as April 2014. *Minimum Qualifications: * - The candidate must hold a Bachelor degree. - Candidate must be fluent in at least one programming language. - A two-year commitment is requested. *Preferred Qualifications: * - Experience using Freesurfer or other neuroimaging platforms. Interested applicants can apply online here: http://www.northwestern.edu/hr/careers/ Job ID: 22916 If you have specific questions please email: e-rogalski(a)northwestern.edu To learn more about our center please go to: www.brain.northwestern.edu -- Emily J Rogalski, PhD Associate Professor Northwestern University Cognitive Neurology and Alzheimer's Disease Center (CNADC) 320 E Superior Street Searle Building 11th Floor Chicago, IL 60611 312-503-1155 phone 312-908-8789 fax erogalski(a)gmail.com

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Freesurfer March 2014