Freesurfer October 2015

freesurfer@nmr.mgh.harvard.edu

142 participants
214 discussions

Re: [Freesurfer] recon-all pipeline for (sub-millimeter) 7T data
by Kendrick Kay 17 Oct '15

17 Oct '15

> Message: 1 > Date: Sat, 17 Oct 2015 11:09:08 -0400 (EDT) > From: Bruce Fischl <fischl(a)nmr.mgh.harvard.edu> > Subject: Re: [Freesurfer] recon-all pipeline for (sub-millimeter) 7T > data > To: Freesurfer support list <freesurfer(a)nmr.mgh.harvard.edu> > Message-ID: > <alpine.LRH.2.20.1510171108090.29644(a)gate.nmr.mgh.harvard.edu> > Content-Type: text/plain; charset="windows-1252" > > High resolution fMRI has always been supported. V6 beta has better support > for high-resolution structurals. If your fMRI is higher than 1mm isotropic > then having higher res structurals (and hence denser cortical meshes) might > be useful Is there a way to obtain denser cortical meshes using the standard FreeSurfer 5.3.0 reconstruction pipeline with 1mm anatomical data? I looked for a flag, but didn't find one.. -- Kendrick Kay, PhD Assistant Professor Center for Magnetic Resonance Research University of Minnesota, Twin Cities Web: http://cvnlab.net <http://cvnlab.net/> E-mail: kay(a)umn.edu <mailto:kay@umn.edu> Cell: 510-206-1059 Skype: kendrickkay

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Re: [Freesurfer] mri_convert with --like and -rt options
by Seung-Goo KIM 16 Oct '15

16 Oct '15

Hi Bruce, Thank you for response. This is the output message: > $ mri_convert -rt nearest --like template.nii.gz label.nii.gz label_nn.nii.gz > mri_convert -rt nearest --like template.nii.gz label.nii.gz label_nn.nii.gz > $Id: mri_convert.c,v 1.179.2.7 2012/09/05 21:55:16 mreuter Exp $ > reading from label.nii.gz... > TR=1000.00, TE=0.00, TI=0.00, flip angle=0.00 > i_ras = (-1, 0, 0) > j_ras = (0, 1, 0) > k_ras = (0, 0, 1) > INFO: transform src into the like-volume: template.nii.gz > writing to label_nn.nii.gz... It doesn’t print out interpolation method for reslicing, which I see when running mri_convert without “—like” switch. And the output (label_nn.nii.gz) has mixed labels due to linear interpolation. Just in case, please find the attached for the header information of the two image files. Best, -SG > Hi Seung-Goo > > I would have that that your command line would work as is. Can you send us the full screen output? > cheers > Bruce > On Fri, 16 Oct 2015, Seung-Goo KIM wrote: > >> Dear all, >> I wish to know whether mri_convert provide a nifty way to reslice and crop a NIFTI >> image with labels (positive integers) with “—like” and “-rt” options. It seems like >> “—like” option overrides “-rt” option, thus the result from such a command: >> >> mri_convert -rt nearest —like ${referenceImage} ${inputImage} >> ${outputImage} >> is resampled with trilinear interpolation. I don’t know if I did something wrong >> (maybe file format?) or this is a bug in mri_convert. >> Of course, one can write a script that creates binary images for each label values, >> transforms it (using "mri_convert —like"), threshold it (like value>0.1), and finally >> finds the label with the highest value (probability) for each voxel in the reference >> space. But I believe there should be a simpler and faster way to do this with >> mri_convert or any other program in freesurfer :) >> FIY, the version of freesurfer package I use is >> "Linux-centos6_x86_64-stable-pub-v5.3.0”. >> Best regards, >> -- >> Seung-Goo KIM -- Seung-Goo KIM

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Using the cluster to speed up tractography
by Li, Baojuan 16 Oct '15

16 Oct '15

Hi Freesurfer experts, I am trying to use the clusters to run BedpostX on a Connectome dataset. Although the job is running now, it is running slowly. It has only got though 18 slices over the last 10 hours: pbsubmit -n 8 -m bl744 -c "bedpostx /space/iggy/5/users/baojuan/mgh_1007/diff/preproc/mri/" As this is the first time I am using the Center's Clusters, I have a few questions and hope someone can kindly help me or give me some suggestions. 1. How many CPUs and Vmem do you usually allocate when running BedpostX on Connectom data? 2. Which queue do you usually use? Do I need to use the extended queue? 3. I checked the jobinfo and found the Walltime is larger than the CPUtime which means the job did not use multiple processors. So could this be the reason? Thanks a lot! Baojuan

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Compiling dev version in ubuntu 15.10
by Chris Adamson 16 Oct '15

16 Oct '15

I'm preparing to migrate over to the new Ubuntu when it comes out. I'm having the following issues compiling it: The included VXL library doesnt compile, using the system version seems to fix this: /usr/pubsw/packages/vxl/current/include/vxl/core/vnl/algo/vnl_symmetric_eigensystem.h:82:1: warning: keyword 'export' not implemented, and will be ignored export template <class T> The inline functions MRIgetVoxVal ... should be defined in the .h file, they are not, I have to comment out the inline versions ../include/mri.h:313:15: warning: inline function 'MRIgetVoxVal' declared but never defined inline float MRIgetVoxVal(const MRI *mri, int c, int r, int s, int f); The included ITK library doesnt have the cxx11 ABI ../utils/libutils.a(mriio_nrrd_itk.o): In function `itk::MemoryAllocationError::MemoryAllocationError(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, unsigned int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)': /usr/pubsw/packages/itk/current/include/InsightToolkit/Common/itkExceptionObject.h:174: undefined reference to `itk::ExceptionObject::ExceptionObject(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, unsigned int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)' ../utils/libutils.a(mriio_nrrd_itk.o):(.rodata._ZTVN3itk24ImageFileReaderExceptionE[_ZTVN3itk24ImageFileReaderExceptionE]+0x40): undefined reference to `itk::ExceptionObject::SetLocation(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)' ../utils/libutils.a(mriio_nrrd_itk.o):(.rodata._ZTVN3itk24ImageFileReaderExceptionE[_ZTVN3itk24ImageFileReaderExceptionE]+0x48): undefined reference to `itk::ExceptionObject::SetDescription(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)' ../utils/libutils.a(mriio_nrrd_itk.o):(.rodata._ZTVN3itk21MemoryAllocationErrorE[_ZTVN3itk21MemoryAllocationErrorE]+0x40): undefined reference to `itk::ExceptionObject::SetLocation(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)' ../utils/libutils.a(mriio_nrrd_itk.o):(.rodata._ZTVN3itk21MemoryAllocationErrorE[_ZTVN3itk21MemoryAllocationErrorE]+0x48): undefined reference to `itk::ExceptionObject::SetDescription(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)' ../utils/libutils.a(mriio_nrrd_itk.o): In function `itk::ImageFileReader<itk::Image<itk::DiffusionTensor3D<float>, 3u>, itk::DefaultConvertPixelTraits<itk::DiffusionTensor3D<float> > >::GenerateOutputInformation()': /usr/pubsw/packages/itk/current/include/InsightToolkit/IO/itkImageFileReader.txx:136: undefined reference to `itk::ObjectFactoryBase::CreateAllInstance[abi:cxx11](char const*)' ../utils/libutils.a(mriio_nrrd_itk.o): In function `itk::ImageFileReader<itk::Image<itk::DiffusionTensor3D<float>, 3u>, itk::DefaultConvertPixelTraits<itk::DiffusionTensor3D<float> > >::DoConvertBuffer(void*, unsigned long)': /usr/pubsw/packages/itk/current/include/InsightToolkit/IO/itkImageFileReader.txx:545: undefined reference to `itk::ImageIOBase::GetComponentTypeAsString[abi:cxx11](itk::ImageIOBase::IOComponentType) const' ../utils/libutils.a(numerics.o):(.rodata._ZTV8fs_lbfgs[_ZTV8fs_lbfgs]+0x28): undefined reference to `vnl_nonlinear_minimizer::is_a[abi:cxx11]() const' ../utils/libutils.a(numerics.o):(.rodata._ZTV8fs_lbfgs[_ZTV8fs_lbfgs]+0x30): undefined reference to `vnl_nonlinear_minimizer::is_class(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) const' ../utils/libutils.a(numerics.o):(.rodata._ZTV9fs_powell[_ZTV9fs_powell]+0x28): undefined reference to `vnl_nonlinear_minimizer::is_a[abi:cxx11]() const' ../utils/libutils.a(numerics.o):(.rodata._ZTV9fs_powell[_ZTV9fs_powell]+0x30): undefined reference to `vnl_nonlinear_minimizer::is_class(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) const' Dr Chris Adamson Research Officer, Developmental Imaging, Murdoch Childrens Research Institute Murdoch Childrens Research Institute Royal Children's Hospital Flemington Road, Parkville, Victoria 3052, Australia www.mcri.edu.au<http://www.mcri.edu.au/> E chris.adamson(a)mcri.edu.au T 03 9936 6780 ______________________________________________________________________ This email has been scanned by the Symantec Email Security.cloud service. For more information please visit http://www.symanteccloud.com ______________________________________________________________________

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Recon-all variations and 3T flag
by Kasper Jessen 16 Oct '15

16 Oct '15

Dear Freesurfer group, - I have noticed different ways of writing the 'recon-all' commands (see below). What is the difference between these two ways of writing the command? Or is it the same? - recon-all -all -s <tpNid> -i path_to_tpN_dcm - recon-all -i <path/anat.nii.gz> -subjid <ID> -all - Does it matter where you place the 3T flag in the command line? fx - recon-all -i <path/ID/anat.nii.gz> -subjid <ID> -3T -all Best regards, Kasper Jessen MD, PhD student

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mri_convert with --like and -rt options
by Seung-Goo KIM 16 Oct '15

16 Oct '15

Dear all, I wish to know whether mri_convert provide a nifty way to reslice and crop a NIFTI image with labels (positive integers) with “—like” and “-rt” options. It seems like “—like” option overrides “-rt” option, thus the result from such a command: > mri_convert -rt nearest —like ${referenceImage} ${inputImage} ${outputImage} is resampled with trilinear interpolation. I don’t know if I did something wrong (maybe file format?) or this is a bug in mri_convert. Of course, one can write a script that creates binary images for each label values, transforms it (using "mri_convert —like"), threshold it (like value>0.1), and finally finds the label with the highest value (probability) for each voxel in the reference space. But I believe there should be a simpler and faster way to do this with mri_convert or any other program in freesurfer :) FIY, the version of freesurfer package I use is "Linux-centos6_x86_64-stable-pub-v5.3.0”. Best regards, -- Seung-Goo KIM

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Possible error in automatic filling of ventricles in wm.mgz
by Antonin Skoch 16 Oct '15

16 Oct '15

Dear FreeSurfer experts, In some subjects I encounter situation where I suspect that the ventricles are not accurately filled in wm.mgz file. I have uploaded the file ventricle_question.tar.gz with example subject to your server so that you can look. It seems to me that in left hemisphere at slices 91-approx 98 (coronal view) the voxels in temporal apex of the left ventricle are not correctly filled by value 250 which has the consequence that the pial and white surfaces are erroneously "digging in" the ventricle (see also the screenshot with arrow marking the suspicious spot). I encounter this situation repeatedly and in most cases it occurs in left hemisphere. Could you please comment on? Will this possible error have an effect to the analyses? Thank you very much for your support! Regards, Antonin Skoch

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Re: [Freesurfer] pial surface encircling the optical chiasm
by Antonin Skoch 16 Oct '15

16 Oct '15

Dear experts, I am sending the example subject named chiasma_question.tar.gz to your FTP server. The issue with encircling chiasma is located in slices ~134-140. According to Aparc.a2009s+aseg the tissue is marked as optical chiasm, but also part of it is labeled as left cerebral white matter. I guess that for the whole-brain group analysis of cortical thickness this error probably will not have an effect since it seems that this region is masked by cortex.label, but in volumetric analyses there could be an effect, although probably very small. Or could this error cause some bias in cortical parcellation in adjacent cortical areas?...What do you think? Regards, Antonin Skoch

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SOLVED - mri_convert segmentation fault after tracula update on Linux/glibc-2.20 (Gentoo)
by Volkmar Glauche 16 Oct '15

16 Oct '15

Dear all, in reply to myself as a documentation for others: I tried a recent development version of mri_convert. Instead of crashing, this version instructed me to get a new license file for systems running GNU glibc version greater 2.15. The new license file (.license, not license.txt) seems to do the trick. Best, Volkmar -- Freiburg Brain Imaging http://fbi.uniklinik-freiburg.de/ Tel. +761 270-54110 Fax. +761 270-53100

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mri_convert segmentation fault after tracula update on Linux/glibc-2.20 (Gentoo)
by Volkmar Glauche 16 Oct '15

16 Oct '15

Dear List, I am facing a similar problem as described by Knut Bjuland: http://www.mail-archive.com/freesurfer%40nmr.mgh.harvard.edu/msg39745.html I could not find a public reply in the mailing list archives. Therefore I would like to know whether it would be safe to either downgrade mri_convert to the version before the tracula update or use a newer development version of mri_convert with Freesurfer 5.3. Best, Volkmar -- Freiburg Brain Imaging http://fbi.uniklinik-freiburg.de/ Tel. +761 270-54110 Fax. +761 270-53100

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Freesurfer October 2015