Freesurfer

freesurfer@nmr.mgh.harvard.edu

16 participants
30084 discussions

(no subject)
by Campanella Martina 18 May '09

18 May '09

Hi freesurfer, We would make a new LUT to create an annot file with personalized names and colours.. How is it possible? Thanks, Martina Campanella

1 0

RE: [Freesurfer] Measuring cortical thickness with high resolution data
by Falk Lüsebrink 18 May '09

18 May '09

Hi Jürgen, We are using a 7T from Siemens and we acquire two volumes with an MPRAGE and 3D GE sequence. Using SPM both volumes are co-registered and afterwards the MPRAGE is divided by the 3D GE. Attached is a sample *.jpg showing the results. In our case the temporal lobes are still not very homogeneous due to some problems with the coil or gradient system (currently a new gradient is being installed, so it probably will help). Also Im further improving the volumes by running mri_nu_correct.mni on the T1.mgz created by the normalization stage (like mri_nu_correct.mni stop 0.001 distance 25 i T1.mgz o nu.mgz) and running mri_normalize again afterwards. The volume normally looks very homogeneous afterwards, even the temporal lobes. But Im facing problems in the following stages, mainly everything based on the aseg files as I need to skip the process. I cant recall exactly during which stage, but recon-all exists with the error that the aseg.mgz needs to be conformed, so it needs to be skipped. But by skipping these stages I currently have issues during mri_fill as the cerebellum is not erased as it should be. Also the skull stripping isnt very good in most cases. The only solution I had was using a brainmask created by Slicer or to run recon-all normally (conforming the data) and resampling the brainmask to the original resolution (using mri_vol2vol). Then masking the T1.mgz to get a fairly good looking brainmask. Hope this helps, Regards, Falk From: Jürgen Hänggi [mailto:j.haenggi@psychologie.uzh.ch] Sent: Monday, May 18, 2009 3:30 PM To: Falk Lüsebrink Subject: Re: [Freesurfer] Measuring cortical thickness with high resolution data Hi Falk We are also struggling with 7T images and Freesurfer. In your email (see below) you wrote that you have find a way to get ride of the inhomogeneities inherent in the 7T images. Which other sequence did you use for that? Do you also use a 7T scanner from Philips? Do you use an adiabatic pulse sequence? Thanks in advance Best regards Jürgen On [DATE], "Falk Lüsebrink" <[ADDRESS]> wrote: Hi Freesurfers, Im trying to evaluate the usefulness of high resolution scans acquired at 7T with an isometric voxel size of .6mm for the measurement of cortical thickness. The inhomogeneities are taken care of by dividing the scans with another scan of another sequence, so they are not an issue anymore. My problem is that Freesurfer usually conforms the voxel size to 1mm which is not desirable. I tried using the cm and noaseg flags for the recon-all process to avoid the conformation and to skip the subcortical segmentation, but another problem arises while using these flags. The error I receive is occurring after the WM Segmentation and states as follows: #-------------------------------------------- #...@# WM Segmentation Wed Mar 18 10:14:42 CET 2009 cp wm.mgz wm.seg.mgz mri_segment -keep brain.mgz wm.seg.mgz preserving editing changes in output volume... doing initial intensity segmentation... using local statistics to label ambiguous voxels... computing class statistics for intensity windows... WM (106.0): 106.9 +- 5.8 [80.0 --> 125.0] GM (69.0) : 66.3 +- 11.6 [30.0 --> 96.0] setting bottom of white matter range to 77.9 setting top of gray matter range to 89.4 doing initial intensity segmentation... using local statistics to label ambiguous voxels... using local geometry to label remaining ambiguous voxels... reclassifying voxels using Gaussian border classifier... removing voxels with positive offset direction... smoothing T1 volume with sigma = 0.250 removing 1-dimensional structures... thickening thin strands.... 20 segments, 4813 filled 10270 bright non-wm voxels segmented. 5589 diagonally connected voxels added... white matter segmentation took 2.4 minutes writing output to wm.seg.mgz... ERROR: mri_segment-MRIcheckVolDims: volume1 height=256 != volume2 height=320. The dimensions of the data Im trying to process is 320 x 320 x 224 and is changed to 320 x 320 x 320 while using the cm flag. It seems the mri_segment process cant handle any dimensions above 256 or Im missing another flag. Does someone has any ideas about that issue? Regards, Falk _____ _______________________________________________ Freesurfer mailing list Freesurfer(a)nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer ---------------------------------------------------------------------------- Juergen Haenggi Ph.D. (Dr. des.) Division 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[at]psychologie.uzh.ch (email) http://www.psychologie.uzh.ch/neuropsy/ (website) http://www.juergenhaenggi.ch (private website) This e-mail (and any attachment/s) contains confidential and/or privileged information. If you are not the intended recipient (or have received this e-mail in error) please notify the sender immediately and destroy this e-mail. Any unauthorised copying, disclosure or distribution of the material in this e-mail is strictly forbidden. ----------------------------------------------------------------------------

1 0

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

18 May '09

p.s. you can pick seed points in the callosum and pons in tkmedit and see if that fixes your problem, but if there is something else going on then it may not (e.g. if the aseg is badly wrong) 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 > >

2 1

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

1 0

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

1 0

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

Jump to page:

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

Freesurfer