Freesurfer

freesurfer@nmr.mgh.harvard.edu

18 participants
30131 discussions

detail of sphere registration
by Zhong Jidan 18 May '09

18 May '09

Hello, After reading the related literature of sphere registration, I have a general idea of the whole process. But I still have some questions about the detail of the registration. Could you give me some hint to my questions ? I really appreciate your time , thanks. The procedure is like: 1, creating the template.tif by mris_make_template. The template you use in Freesurfer is created by iterative registration of 40 subjects, according to "High-resolution inter-subject averaging and a coordinate system for the cortical surface, Fischl, B., Sereno, M.I., Tootell, R.B.H., and Dale, A.M., (1999). Human Brain Mapping, 8:272-284(1999)". So, after the template generation process, you will get a .tif file which include the necessary infomation (like the means and variances of curv, sul from the aligned spheres). But,do you have the other information of this final template, such as the sphere representation, folded surface representation of this template? I know that under */subjects/fsaverage/surf, there are some surface representations of the average of the 40 subjects, but to my knowledge, they are just used for visulazation and are not the surface representation of the template.tif you used, am I right? 2, do subjects' sphere registration to the template sphere get the deformed subjects spheres( *.reg ), which have a one-to-one correspondance to the original subject surfaces. Except the .reg sphere with the cuvature information, do you have any other form of representation of the deformed sphere? You know that there are other kinds of surface mapping methods, like Miller's Large Defformation deffeomrphic surface mapping, they just do surface mapping using the folded surfaces. After surface mapping, they will get the deformed folded surface which would be aligned with the template folded surface. With the deformed subject and template folded surfaces, they can tell directly which sulcus or gyrus is aligned well. So, for your mapping, when I get the deformed sphere, do you have any command or method to put the sphere back to the folded surface so I can see the suci and gyri directly? If you also have the surface representation of the template, then i can superimpose them to see how good the alignment is. In fact, I found one reference using your sphere registration method. "Simpliﬁed Intersubject Averaging on the Cortical Surface Using SUMA"Brenna D. Argall, Ziad S. Saad,and Michael S. Beauchamp"Human Brain Mapping 27:14 –27(2006)" Please see the attachment. In "Spherical Morphing" section, They mentioned that " Using the mris_register [Fischl et al., 1999b] routine, each individual subject’s surface was registered to the FreeSurfer average7 template prior to node number standardization. Standardization and averaging were then performed on the surfaces as described above" (using SUMA FYI). ---- From this part, I assume that all the deformed surfaces are in spherical representation. Then in the result part, in section "Intersubject Averaging of Functional Data: Different Surface Methods", they mentioned they " in order to compare the AC–PC method to these more complex algorithms, the FreeSurfer program mris_register [used in Fischl et al., 1999b] was used to morph the cortical surface models to a predeﬁned template, and these morphed surface models were then used to create a morphed surface average." In Fig7C ：Average surface created by averaging the same 28 subjects using mris_register standardization. You can see that they show the average surface in a folded surface representation, not a sphere. Could you give me a hint that how they do this since you only have a sphere representation of the aligned surface? -- Regards, Jidan

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Re: [Freesurfer] mri_fill
by Bruce Fischl 18 May '09

18 May '09

hmm, this almost never fails anymore. What does the aseg look like? Did it label things correctly? Is the skull stripping ok? Bruce On Mon, 18 May 2009, Falk Lüsebrink wrote: > Hi FreeSurfers, > > > > At the end of mri_fill Im told to check the filled volume as the cerebellum > may be included. It is and also the brainstem. But actually I dont know > how to fix this. Do I need to include the seed points for cc and pons for > better cutting planes? Do I need to manually edit the volume? > > > > If the latter is better are there any other tools available besides tkmedit? > If I try to add or delete voxels of a high resolution volume tkmedit seems > to skin every second slice. > > > > Regards, > > Falk > >

1 0

mri_fill
by Falk Lüsebrink 18 May '09

18 May '09

Hi FreeSurfers, At the end of mri_fill Im told to check the filled volume as the cerebellum may be included. It is and also the brainstem. But actually I dont know how to fix this. Do I need to include the seed points for cc and pons for better cutting planes? Do I need to manually edit the volume? If the latter is better are there any other tools available besides tkmedit? If I try to add or delete voxels of a high resolution volume tkmedit seems to skin every second slice. Regards, Falk

1 0

pial edit on atrophied temporal pole
by Olivier Piguet 15 May '09

15 May '09

Hi there, I've run autorecon2 on a subject who has significant unilateral atrophy in the anterior temporal region. In the last few slices anteriorly, the pial surface does not include what is clearly atrophied cortical tissue without underlying white matter. What is the method to correct for this? Looking at previous queries, all of them refer to spots where one can manipulate the segmentation by adding control points in the neighbouring white matter, which is not present in this instance. Any suggestion appreciated. Olivier ~~~~~~~~~~~~~~~~~~~~~ Olivier Piguet Ph.D. NHMRC Fellow (Clinical Career Development Award) Conjoint Senior Lecturer UNSW Prince of Wales Medical Research Institute Barker St Randwick NSW 2031 Australia Voice: +61 2 9399 1113 Fax: +61 2 9399 1047 E-mail: o.piguet(a)powmri.edu.au <pastedGraphic.tiff> http://www.ftdrg.org/

3 9

mri_convert: correspondence between structure values when I convert to minc file
by Paula Diniz 15 May '09

15 May '09

Hello! I have to convert the aseg.mgz file to a minc file, but I lost the structure values reference. Where I can find a convertion table or how I make to recover the structures values reference? Thanks! -- ================================== Paula Rejane Beserra Diniz Bacharel em Informática Biomédica Mestre em Neurociências Doutoranda em Neurociências Universidade de São Paulo Hospital das Clínicas - Ribeirão Preto ==================================

3 4

mri_ca_train on primate data
by Kevin Scheibel 15 May '09

15 May '09

Hello, I am preparing a dataset of 42 segmented vervet brains to make an aseg atlas using mri_ca_train. A couple of quick questions: 1. Does every voxel need to be labeled for mri_ca_train to create a robust atlas? E.g., we have not manually segmented out white matter or cerebral cortex in our brains. Is this necessary? 2. Can I create a .gca file with mri_ca_train that can then be used by mri_ca_label to label a novel dataset without having to use rebuild_gca_atlas.csh? Thanks! Kevin Scheibel k.scheibel(a)ucla.edu

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Re: zero determinant error in using mri_convert rawavg.mgz orig.mgz --conform
by John Drozd 15 May '09

15 May '09

> Hello, > > Here is the ouput from bugr: > > FREESURFER_HOME: /trumpet/downloads/FreeSurfer/freesurfer > > Build stamp: freesurfer-Linux-centos4_x86_64-stable-pub-v4.3.0 > > RedHat release: Fedora release 10 (Cambridge) > > Kernel info: Linux 2.6.27.21-170.2.56.fc10.x86_64 x86_64 > > I have sets of dicom files such as: > > [jdrozd@trumpet orig]$ ls > 70731171155016_S32496_I63397_0.dcm* 70731171155016_S32496_I63397_25.dcm* > 70731171155016_S32496_I63397_100.dcm* 70731171155016_S32496_I63397_26.dcm* > 70731171155016_S32496_I63397_101.dcm* 70731171155016_S32496_I63397_27.dcm* > 70731171155016_S32496_I63397_102.dcm* 70731171155016_S32496_I63397_28.dcm* > 70731171155016_S32496_I63397_103.dcm* 70731171155016_S32496_I63397_29.dcm* > 70731171155016_S32496_I63397_104.dcm* 70731171155016_S32496_I63397_2.dcm* > 70731171155016_S32496_I63397_105.dcm* 70731171155016_S32496_I63397_30.dcm* > 70731171155016_S32496_I63397_106.dcm* 70731171155016_S32496_I63397_31.dcm* > 70731171155016_S32496_I63397_107.dcm* 70731171155016_S32496_I63397_32.dcm* > 70731171155016_S32496_I63397_108.dcm* 70731171155016_S32496_I63397_33.dcm* > 70731171155016_S32496_I63397_109.dcm* 70731171155016_S32496_I63397_34.dcm* > 70731171155016_S32496_I63397_10.dcm* 70731171155016_S32496_I63397_35.dcm* > 70731171155016_S32496_I63397_110.dcm* 70731171155016_S32496_I63397_36.dcm* > 70731171155016_S32496_I63397_111.dcm* 70731171155016_S32496_I63397_37.dcm* > 70731171155016_S32496_I63397_112.dcm* 70731171155016_S32496_I63397_38.dcm* > 70731171155016_S32496_I63397_113.dcm* 70731171155016_S32496_I63397_39.dcm* > 70731171155016_S32496_I63397_114.dcm* 70731171155016_S32496_I63397_3.dcm* > 70731171155016_S32496_I63397_115.dcm* 70731171155016_S32496_I63397_40.dcm* > 70731171155016_S32496_I63397_116.dcm* 70731171155016_S32496_I63397_41.dcm* > 70731171155016_S32496_I63397_117.dcm* 70731171155016_S32496_I63397_42.dcm* > 70731171155016_S32496_I63397_118.dcm* 70731171155016_S32496_I63397_43.dcm* > 70731171155016_S32496_I63397_119.dcm* 70731171155016_S32496_I63397_44.dcm* > 70731171155016_S32496_I63397_11.dcm* 70731171155016_S32496_I63397_45.dcm* > 70731171155016_S32496_I63397_120.dcm* 70731171155016_S32496_I63397_46.dcm* > 70731171155016_S32496_I63397_121.dcm* 70731171155016_S32496_I63397_47.dcm* > 70731171155016_S32496_I63397_122.dcm* 70731171155016_S32496_I63397_48.dcm* > 70731171155016_S32496_I63397_123.dcm* 70731171155016_S32496_I63397_49.dcm* > 70731171155016_S32496_I63397_124.dcm* 70731171155016_S32496_I63397_4.dcm* > 70731171155016_S32496_I63397_125.dcm* 70731171155016_S32496_I63397_50.dcm* > 70731171155016_S32496_I63397_126.dcm* 70731171155016_S32496_I63397_51.dcm* > 70731171155016_S32496_I63397_127.dcm* 70731171155016_S32496_I63397_52.dcm* > 70731171155016_S32496_I63397_128.dcm* 70731171155016_S32496_I63397_53.dcm* > 70731171155016_S32496_I63397_129.dcm* 70731171155016_S32496_I63397_54.dcm* > 70731171155016_S32496_I63397_12.dcm* 70731171155016_S32496_I63397_55.dcm* > 70731171155016_S32496_I63397_130.dcm* 70731171155016_S32496_I63397_56.dcm* > 70731171155016_S32496_I63397_131.dcm* 70731171155016_S32496_I63397_57.dcm* > 70731171155016_S32496_I63397_132.dcm* 70731171155016_S32496_I63397_58.dcm* > 70731171155016_S32496_I63397_133.dcm* 70731171155016_S32496_I63397_59.dcm* > 70731171155016_S32496_I63397_134.dcm* 70731171155016_S32496_I63397_5.dcm* > 70731171155016_S32496_I63397_135.dcm* 70731171155016_S32496_I63397_60.dcm* > 70731171155016_S32496_I63397_136.dcm* 70731171155016_S32496_I63397_61.dcm* > 70731171155016_S32496_I63397_137.dcm* 70731171155016_S32496_I63397_62.dcm* > 70731171155016_S32496_I63397_138.dcm* 70731171155016_S32496_I63397_63.dcm* > 70731171155016_S32496_I63397_139.dcm* 70731171155016_S32496_I63397_64.dcm* > 70731171155016_S32496_I63397_13.dcm* 70731171155016_S32496_I63397_65.dcm* > 70731171155016_S32496_I63397_140.dcm* 70731171155016_S32496_I63397_66.dcm* > 70731171155016_S32496_I63397_141.dcm* 70731171155016_S32496_I63397_67.dcm* > 70731171155016_S32496_I63397_142.dcm* 70731171155016_S32496_I63397_68.dcm* > 70731171155016_S32496_I63397_143.dcm* 70731171155016_S32496_I63397_69.dcm* > 70731171155016_S32496_I63397_144.dcm* 70731171155016_S32496_I63397_6.dcm* > 70731171155016_S32496_I63397_145.dcm* 70731171155016_S32496_I63397_70.dcm* > 70731171155016_S32496_I63397_146.dcm* 70731171155016_S32496_I63397_71.dcm* > 70731171155016_S32496_I63397_147.dcm* 70731171155016_S32496_I63397_72.dcm* > 70731171155016_S32496_I63397_148.dcm* 70731171155016_S32496_I63397_73.dcm* > 70731171155016_S32496_I63397_149.dcm* 70731171155016_S32496_I63397_74.dcm* > 70731171155016_S32496_I63397_14.dcm* 70731171155016_S32496_I63397_75.dcm* > 70731171155016_S32496_I63397_150.dcm* 70731171155016_S32496_I63397_76.dcm* > 70731171155016_S32496_I63397_151.dcm* 70731171155016_S32496_I63397_77.dcm* > 70731171155016_S32496_I63397_152.dcm* 70731171155016_S32496_I63397_78.dcm* > 70731171155016_S32496_I63397_153.dcm* 70731171155016_S32496_I63397_79.dcm* > 70731171155016_S32496_I63397_154.dcm* 70731171155016_S32496_I63397_7.dcm* > 70731171155016_S32496_I63397_155.dcm* 70731171155016_S32496_I63397_80.dcm* > 70731171155016_S32496_I63397_156.dcm* 70731171155016_S32496_I63397_81.dcm* > 70731171155016_S32496_I63397_157.dcm* 70731171155016_S32496_I63397_82.dcm* > 70731171155016_S32496_I63397_158.dcm* 70731171155016_S32496_I63397_83.dcm* > 70731171155016_S32496_I63397_159.dcm* 70731171155016_S32496_I63397_84.dcm* > 70731171155016_S32496_I63397_15.dcm* 70731171155016_S32496_I63397_85.dcm* > 70731171155016_S32496_I63397_160.dcm* 70731171155016_S32496_I63397_86.dcm* > 70731171155016_S32496_I63397_161.dcm* 70731171155016_S32496_I63397_87.dcm* > 70731171155016_S32496_I63397_162.dcm* 70731171155016_S32496_I63397_88.dcm* > 70731171155016_S32496_I63397_163.dcm* 70731171155016_S32496_I63397_89.dcm* > 70731171155016_S32496_I63397_164.dcm* 70731171155016_S32496_I63397_8.dcm* > 70731171155016_S32496_I63397_165.dcm* 70731171155016_S32496_I63397_90.dcm* > 70731171155016_S32496_I63397_16.dcm* 70731171155016_S32496_I63397_91.dcm* > 70731171155016_S32496_I63397_17.dcm* 70731171155016_S32496_I63397_92.dcm* > 70731171155016_S32496_I63397_18.dcm* 70731171155016_S32496_I63397_93.dcm* > 70731171155016_S32496_I63397_19.dcm* 70731171155016_S32496_I63397_94.dcm* > 70731171155016_S32496_I63397_1.dcm* 70731171155016_S32496_I63397_95.dcm* > 70731171155016_S32496_I63397_20.dcm* 70731171155016_S32496_I63397_96.dcm* > 70731171155016_S32496_I63397_21.dcm* 70731171155016_S32496_I63397_97.dcm* > 70731171155016_S32496_I63397_22.dcm* 70731171155016_S32496_I63397_98.dcm* > 70731171155016_S32496_I63397_23.dcm* 70731171155016_S32496_I63397_99.dcm* > 70731171155016_S32496_I63397_24.dcm* 70731171155016_S32496_I63397_9.dcm* > > I first converted these files to an mgz file using: > > [jdrozd@trumpet orig]$ mri_convert -it dicom > 70731171155016_S32496_I63397_0.dcm T1.mgz > mri_convert -it dicom 70731171155016_S32496_I63397_0.dcm T1.mgz > $Id: mri_convert.c,v 1.146.2.4 2009/01/30 02:30:42 nicks Exp $ > reading from 70731171155016_S32496_I63397_0.dcm... > Starting DICOMRead2() > dcmfile = > /trumpet/downloads/FreeSurfer/freesurfer/subjects/buckner_data/tutorial_subjs/convertedfile/mri/orig/70731171155016_S32496_I63397_0.dcm > dcmdir = > /trumpet/downloads/FreeSurfer/freesurfer/subjects/buckner_data/tutorial_subjs/convertedfile/mri/orig > WARNING: tag ImageNumber not found > Ref Series No = 63443 > Found 168 files, checking for dicoms > WARNING: tag ImageNumber not found > Found 166 dicom files in series. > WARNING: tag ImageNumber not found > First Sorting > WARNING: files are not found to be different and cannot be sorted > File1: > /trumpet/downloads/FreeSurfer/freesurfer/subjects/buckner_data/tutorial_subjs/convertedfile/mri/orig/70731171155016_S32496_I63397_0.dcm > File2: > /trumpet/downloads/FreeSurfer/freesurfer/subjects/buckner_data/tutorial_subjs/convertedfile/mri/orig/70731171155016_S32496_I63397_1.dcm > Computing Slice Direction > Vs: 1.2024 0 0 > Vs: 1 0 0 > Second Sorting > Counting frames > nframes = 1 > nslices = 166 > ndcmfiles = 166 > PE Dir = UNKNOWN (dicom read) > TransferSyntaxUID: --1.2.840.10008.1.2-- > jpegUID: --1.2.840.10008.1.2.4-- > Loading pixel data > TR=0.00, TE=0.00, TI=0.00, flip angle=0.00 > i_ras = (-0, -0, -1) > j_ras = (-0, -1, 0) > k_ras = (-1, -0, 0) > writing to T1.mgz... > > Then I copied the outputted T1.mgz file using: > > [jdrozd@trumpet orig]$ cp T1.mgz ../rawavg.mgz > [jdrozd@trumpet orig]$ cd .. > [jdrozd@trumpet mri]$ ls > 1.Bvq.Xml* 2.Bvq.Xml* error.log orig/ orig2/ rawavg.mgz transforms/ > [jdrozd@trumpet mri]$ pwd > > /trumpet/downloads/FreeSurfer/freesurfer/subjects/buckner_data/tutorial_subjs/convertedfile/mri > > Then I tried to conform the data using: > > [jdrozd@trumpet mri]$ mri_convert rawavg.mgz orig.mgz --conform > mri_convert rawavg.mgz orig.mgz --conform > $Id: mri_convert.c,v 1.146.2.4 2009/01/30 02:30:42 nicks Exp $ > reading from rawavg.mgz... > TR=0.00, TE=0.00, TI=0.00, flip angle=0.00 > i_ras = (-0, -0, -1) > j_ras = (-0, -1, 0) > k_ras = (-1, -0, 0) > Original Data has (0.93905, 0.93905, 0) mm size and (256, 256, 166) voxels. > Data is conformed to 1 mm size and 256 voxels for all directions > changing data type from 4 to 0 (noscale = 0)... > MRIchangeType: Building histogram > Reslicing using trilinear interpolation > MRIresample(): source matrix has zero determinant; matrix is: > -0.000 -0.000 -0.000 0.000; > -0.000 -0.939 -0.000 0.000; > -0.939 0.000 0.000 0.000; > 0.000 0.000 0.000 1.000; > > Do you know why I get this error? > MRIresample(): source matrix has zero determinant; matrix is: > -0.000 -0.000 -0.000 0.000; > -0.000 -0.939 -0.000 0.000; > -0.939 0.000 0.000 0.000; > 0.000 0.000 0.000 1.000; > > Any help would be appreciated. > > John Drozd > PostDoctorate Fellow >

4 6

data conversion
by Al-Radaideh Ali 15 May '09

15 May '09

Dear FreeSurfer experts, I used 0.6mm isotropic resolution MPRAGE ( matrix size 320 x 320 ) and 260 slices in freesurfer. The output (.mgz) has a different resolution and matrix size (1mm isotropic resolution and 256 x 256 matrix size). I used mri_convert to convert the output image from mgz to analyze. is there any way I can get back to the original resolution and matrix size, please? Thanks in advance Ali This message has been checked for viruses but the contents of an attachment may still contain software viruses, which could damage your computer system: you are advised to perform your own checks. Email communications with the University of Nottingham may be monitored as permitted by UK legislation.

2 1

Processing high resolution data
by Falk Lüsebrink 15 May '09

15 May '09

Hi FreeSurfers, Im still trying to process some high resolution data through the freesurfer stream, but it is constantly failing during several different stages. The biggest issue is the skull stripping and Im still trying to get good results here. Using the hires switch during autorecon1 normally leaves to much skull or cuts of too much tissue. Adjusting the parameters during mri_watershed (like changing the preflooding height or using the atlas switch) doesnt work too well in most cases. I tried to manually edit the brainmask.mgz with tkmedit but I encountered another problem. I was using data with an isometric voxel size of 0.6mm and removed every bit of left skull from the coronal view. Afterwards I ran autorecon2 but it did exit, so I viewed the brainmask in Slicer and noticed that probably every second slice was skipped in tkmedit. I also tried using the cm switch during autorecon1 to create the .lta file for the skull stripping stage, which I was hoping to improve the results. But either mri_watershed exists with an error in which it states that the WM intensity is 0 and therefore below the csf intensity and that I should check the volume, though I cant find anything unusual, or it exists with the error segmentation fault. I read that these segmentation fault errors seem to occur if the system runs out of memory, but as Im having 32gb ram and 16gb swap memory I dont think this is the reason. Another approach I was using is to use either a brainmask created by a stream of Slicer and then importing it to freesurfer or to use a brainmask created by a conformed stream, then using mri_vol2vol to resample it to the original resolution and process the other stages. The first approach should work fine, but the volume I used wasnt well processed during mri_fill. Most voxels were recognized as being part of the left hemisphere and only a few (about 150) were marked as belonging to the right hemisphere. And I was unable to fix this issue. The second approach seems also to be a good idea, but the resulting brainmask is blurred due to the upscaling. I noticed that using the hires switch the brainmask isnt really used as a mask during normalization2 but is just normalized again and the output is written as brain.mgz. If I want to use the brainmask as a mask (as it should be intended) should I use it to mask the T1.mgz? Like mri_normalize noconform mask brainmask.mgz T1.mgz brain.mgz? In the original stream the brainmask is used here to mask the norm.mgz, which I quite dont understand as the norm.mgz is already stripped. But maybe I just get something wrong. Yesterday I was able get a good skull stripping by running mri_nu_correct again with T1.mgz as the input and using the distance 25 stop 0.0001 switches (which I read of in another mail here on the list to improve results using 3T data). But recon-all exists at the beginning of mris_fix_topology with the segmentation fault error on both hemispheres. I apologize for the long text, but maybe someone can give me some input to try something else or help with existing issues. Thanks in advance, Regards, Falk

1 0

segmentation
by Feng-Xian 14 May '09

14 May '09

Hi, I have some problem. Could you get me some suggestion? I get a simulation brain with no-adding noise from BrainWeb. Then, I add 1% noise and 5% noise, respectively, to the simulation brains. When I finished these simulation brains through FreeSurfer, I found that the cortical thickness of these two groups (1% vs 5%) has a bias. Would you get me some comment? I guess the finding of bias maybe has a great relationship with the process of segmentation. Would you tell me what to do segmentation in FreeSuefer? Thank you in advance! Feng-Xian ------------------------------------------------- Chang Gung University Mail Server Web Mail system By Chang-Gung University Information Center (http://www.cgu.edu.tw/ic/)

1 0

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