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freesurfer@nmr.mgh.harvard.edu

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30063 discussions

Tracula --- Volume and path length are equal
by Mehta, Chintan 23 Oct '17

23 Oct '17

Dear FreeSurfer users, I am using FreeSurfer 6.0 and Tracula 6.0. For many subjects that I'm processing, the volume and path length are equal to each other. For ~60% of subjects, the "pathstats.overall.txt" file shows something like: Count 1500 Volume 34 Len_Min 34 Len_Max 34 Len_Avg 34 Len_Center 34 AD_Avg 0.00104677 AD_Avg_Weight 0.00104677 AD_Avg_Center 0.00104677 RD_Avg 0.000594649 RD_Avg_Weight 0.000594649 RD_Avg_Center 0.000594649 MD_Avg 0.000745357 MD_Avg_Weight 0.000745357 MD_Avg_Center 0.000745357 FA_Avg 0.364984 FA_Avg_Weight 0.364984 FA_Avg_Center 0.364984 This output suggests that only a single pathway was computed for a subject with output like above (since Len_Min = Len_Max = Len_Avg = Len_Center); yet the count number suggests that 1,500 paths were generated. This obviously seems problematic. I have two questions: 1) Does the problem originate during the fitting of the ball-and-stick models at each voxel? (I used n=3 sticks with bedpostx). If so, how can I rerun this process to ensure this problem does not repeat? 2) Is it possible that each probabilistic track was generated with the same random seed? If so, would this problem be associated with the ball-and-stick model step (with bedpostx_gpu) or pathway fitting step (-path)? 3) Are the anisotropy measures (such as FA_Avg, MD_Avg_Weight, etc) independent of this problem? Or do they also require different probabilistic paths be generated? I suspect this issue may have arisen due to my using "bedpostx_gpu" to fit the ball-and-stick models (default setting). Thank you much in advance. Best, Chintan

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Help with extraction of cortical thickness from ROI and creation of mask.
by Dennis M. Hedderich 23 Oct '17

23 Oct '17

Dear Freesurfer Team, I built a GLM, did a 2 sample t-test and found significant differences in cortical thickness in the right middle temporal gyrus between two groups. Now, I would like to kindly ask for your help with two problems that I am facing: 1) for further correlation analyses in SPSS, I would like to extract cortical thickness exactly from the region of difference in the middle temporal gyrus of every subject. Extraction of cortical thickness of the whole middle temporal gyrus worked well, however there is a lot of noise in that information because the area of significant difference is a lot smaller than the MTG roi from the Desikan atlas. 2) to assess thalamocortical structural connectivity to that region, I would like to create and extract a mask in MNI space that I could use with fsl. Is that possible? Thank you very much in advance for any kind of help. Best wishes, Dennis

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Wm edits and wm surface
by Maksimovskiy, Arkadiy 22 Oct '17

22 Oct '17

Hi Everyone, I looked through archived messages, and even though this was mentioned, I did not quiet find a clear response. Is it necessary to make edits to the wm volume if the wm surface is accurate? For example, if the surface follows the wm boundary accurately, but the wm volume has 1. some extra voxels filled outside of the brain or 2. Wm has some voxels not filled inside of it. Any information would be greatly appreciated. Thanks, Arkadiy

2 1

apply transformation using talairach.m3z
by Gidon Levakov 22 Oct '17

22 Oct '17

Hi Freesurfer experts, I have several nifti images (created with another software) in the subjects original anatomical space (native space) that I want to transform to a common space (freesurfer version of MNI305 should be fine) using non-linear transformation. Reading a previous answer regarding this issue ( https://mail.nmr.mgh.harvard.edu/pipermail//freesurfer/2013-September/03355…) I understand I should use the *mri_vol2vol* command to apply the transformation stored in the file *mri/transforms/talairach.m3z* (I already run recon all). But after checking the result, the images are still not align with each other and do not resemble the *mni305.cor.mgz* file. I used the following command: mri_vol2vol --m3z my_subjects_dir/sub_X/mri/transforms/talairach.m3z --noDefM3zPath --reg_header --mov file_loc/img.nii.gz --targ /usr/local/freesurfer/average/mni305.cor.mgz --o file_loc/img_warped.nii.gz I also tried without the --reg_header option with no success. Any idea what I am doing wrong? can you give me an example that works? Thanks in advance! Gidon l.

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mri_cvs_register error
by miracle ozzoude 21 Oct '17

21 Oct '17

Hello, I am trying to run mri_cvs_register on a subject and I got an error (please see attached log file). Below was the command I used. Thank you. mri_cvs_register --mov 01091p --mni --step1 --step2 --step3 --outdir /Users/MiracleOz/Documents/improvervsdeclinermri/01091p/cvs --asegfname aparc+aseg --openmp 1 Best, Paul

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Re: [Freesurfer] Recon-all for Allen Brain Institute T1 image
by Melanie Ganz 21 Oct '17

21 Oct '17

1 0

seek help
by 辛雨萌 21 Oct '17

21 Oct '17

Dear FreeSurfer Experts, I'm a beginner in cognitive neuronscience and so new to the FreeSurfer. Recently I got some datas from AFNI, and in the documents I only found some surfaces that had been created by FreeSurfer. However, the documents only include some resting state volumes without the structural volumes. The format of the surfaces is ".asc", they can be opened by FreeSurfer. But turn to the cortical parcellation, there is only a file called "XXX.annot.niml.dset" and cannot be opened in the freeview or tktools. I'm wondering how can I get the cortical parcellation and stats about the cortical thickness from these files? Thank you!

2 1

lta_convert does not produce ITK transforms that are correctly applied by antsApplyTransforms
by Christopher Markiewicz 20 Oct '17

20 Oct '17

Hi, I've used `bbregister` to generate a transform `bold2T1.lta` from `bold.nii` to `T1.mgz` (assume we have a `T1.nii` as well for the sake of ANTs). The following produces a well-aligned output: mri_convert --apply_transform bold2T1.lta bold.nii bold_space-T1.nii As does the following: lta_convert --inlta bold2T1.lta --outfsl bold2T1.mat c3d_affine_tool -ref T1.nii -src bold.nii bold2T1.mat -fsl2ras -oitk bold2T1.txt antsApplyTransforms -i bold.nii -r T1.nii -o bold_space-T1.nii -t bold2T1.txt However, if one skips the FSL step, the registration is quite far off: lta_convert --inlta bold2T1.lta --outitk bold2T1.txt antsApplyTransforms -i bold.nii -r T1.nii -o bold_space-T1.nii -t bold2T1.txt Comparing the ITK transform files: LTA-FSL-ITK #Insight Transform File V1.0 #Transform 0 Transform: MatrixOffsetTransformBase_double_3_3 Parameters: 0.9895096215486424 0.011126830936108464 -0.00042204653562094823 -0.01079971161879626 0.872329255299452 -0.42602926756857834 -0.004755964529051335 0.42420535065804454 0.8878552541301569 -1.3066136395454464 -45.60342165876236 -43.10584860730749 FixedParameters: 0 0 0 LTA-ITK #Insight Transform File V1.0 #Transform 0 Transform: AffineTransform_double_3_3 Parameters: 0.98950976133346558 0.011126830242574215 -0.00042204943019896746 -0.010799713432788849 0.87232941389083862 -0.42602935433387756 -0.0047559700906276703 0.42420542240142822 0.88785547018051147 -2.2848172187805176 -2.9065067768096924 11.744022369384766 FixedParameters: 0 0 0 To 5 significant digits, these are the same, except the last three (translation) parameters. And the `AffineTransform_double_3_3` is different from `MatrixOffsetTransformBase_double_3_3`, though I'm not sure whether this has any effect. Here is the original LTA: type = 1 # LINEAR_RAS_TO_RAS nxforms = 1 mean = 0.0000 0.0000 0.0000 sigma = 1.0000 1 4 4 1.010462999343872e+00 -1.063966564834118e-02 4.625014495104551e-03 -2.332115173339844e+00 1.228639855980873e-02 9.293417930603027e-01 -4.459420144557953e-01 2.507942199707031e+00 4.575361963361502e-04 4.440840482711792e-01 9.132194519042969e-01 -1.201664733886719e+01 0.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00 9.999998807907104e-01 src volume info valid = 1 # volume info valid filename = /scratch/fmriprep_wf/single_subject_02_wf/func_preproc_task_short_wf/bold_reg_wf/bbreg_wf/bbregister/uni_masked_xform.nii.gz volume = 64 64 34 voxelsize = 3.125000000000000e+00 3.125000000000000e+00 4.000000000000000e+00 xras = -1.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00 yras = 0.000000000000000e+00 1.000000000000000e+00 0.000000000000000e+00 zras = 0.000000000000000e+00 0.000000000000000e+00 1.000000000000000e+00 cras = -1.090248107910156e+00 -1.071614074707031e+01 1.619928741455078e+01 dst volume info valid = 1 # volume info valid filename = /scratch/fmriprep_wf/single_subject_02_wf/anat_preproc_wf/t1_merge/sub-02_T1w_template.nii.gz volume = 160 192 192 voxelsize = 1.000000000000000e+00 1.333333015441895e+00 1.333333015441895e+00 xras = 1.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00 yras = 0.000000000000000e+00 1.000000000000000e+00 0.000000000000000e+00 zras = 0.000000000000000e+00 0.000000000000000e+00 1.000000000000000e+00 cras = -3.000000000000000e+00 2.999969482421875e+00 -8.000030517578125e+00 subject sub-02 fscale 0.100000 If it would be useful, I can provide any relevant images for testing. -- Chris Markiewicz Center for Reproducible Neuroscience Stanford University

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Re: [Freesurfer] Recon-all for Allen Brain Institute T1 image
by Sean Froudist Walsh 20 Oct '17

20 Oct '17

That would be great Melanie, thank you very much. And thanks to Bruce and Satra for the quick responses. How will I be able to find the processed files? Will it be announced somehow? Best wishes, Sean

1 0

asking for literature
by Jiook Cha 20 Oct '17

20 Oct '17

Hello, Could anybody please point me to a paper/asbtract showing meaningful improvement of pial surface segmentation using additional T2 or Flair images in the recon-all procedure? Thanks, Jiook ᐧ

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