Freesurfer August 2014

freesurfer@nmr.mgh.harvard.edu

146 participants
208 discussions

cortical thickness analysis
by Xinfa Shi 30 Aug '14

30 Aug '14

Hi , I want to make a cortical thickness analysis ,and could you provide me for a user guide or tool ? Regards. Xin-Fa Shi.

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Longitudinal troubleshooting
by Janosch Linkersdörfer 29 Aug '14

29 Aug '14

Hi Martin and all, I am about to process a large longitudinal dataset (normal development, no patients) and wanted to ask about the best (i.e., time efficient) strategy for troubleshooting. If I understand correctly from https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalEdits, it might be OK in my case (only little longitudinal changes expected) to only edit the base runs and transfer those edits to the long runs. So I thought of doing the following: - use the QA tools to export detailed snapshots of all base runs - check the snapshots for errors - use Freeview to add control points / edit white matter in brainmask.mgz of the base runs (while simultaneously checking whether those edits would make sense in brainmask.mgz of all long runs of the same subject) - rerun base - rerun longs Does that make sense? Thanks, Janosch

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Reconstruct tm3d warp from mri_cvs_register
by Makaretz, Sara Johanna 29 Aug '14

29 Aug '14

Hi all, I ran mri_cvs_register but forgot to add --nocleanup. I have the final combined m3z and no tm3d, and for el_reg just mgz files. Can I recreate the tm3d combined with just these files? On the wiki it says use createMorph - I tried different inputs in 5.3 and dev environments with no success. (https://surfer.nmr.mgh.harvard.edu/fswiki/mri_cvs_register) Thanks, Sara

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Re: [Freesurfer] recon-all normalization: bias field output
by Barbara Kreilkamp 29 Aug '14

29 Aug '14

Dear Freesurfers, The recon-all.log does not give info about the intermediate outputs (like nu2_est and nu2_field mnc-files), could you please confirm that the nu2_field.mnc is the bias field volume? It is the biggest file of all and is one of the last files generated by the script, but I would like to be sure. Thank you very much, Barbara On Thu, Aug 28, 2014 at 3:27 PM, Barbara Kreilkamp <bakk.hbg(a)googlemail.com> wrote: > Dear Bruce and Christian, > > I found the easy way of simply writing 'set cleanup = 0' at the beginning > of mri_nu_correct.mni and then I run this command > mri_nu_correct.mni --i T2-scic/mri/orig/001.mgz --o nu.mgz --n 2 > > This way I get all the masks and iterations that were computed. > > Now I also see that it generates as many folders as there are iterations, > ending with nu2_field and nu2_est if there are two iterations. I see more > files now and now I am thinking that the last output is nu2_field, which > would be the bias field. > So this is why I did not divide anything by hand (also because my 001.mgz > and the nu.mgz do not have the same image dimensions) and the info about > masked-out voxel would be missing in that case. > > All the best and thanks. > Barbara > > > > On 28/08/2014 14:46, Bruce Fischl wrote: > >> Hi Barbara >> what exactly did you divide? If you look at the recon-all.log it will >> show the exact inputs and outputs of nu_correct. >> >> cheers >> Bruce >> >> >> On Thu, 28 Aug 2014, Barbara Kreilkamp wrote: >> >> Dear Christian, >>> >>> Thanks a bunch for this answer. I ran all the steps you mentioned >>> (except for the one where I simply do uncorrected/corrected, as these >>> images have different dimensions, it seems nu3 does more than just >>> normalization of intensities, but also image cropping). Do you know >>> anything about the image cropping? >>> >>> I ended up with the output nu1_mask and nu1_est and I think the last one >>> is the bias field, at least it looks very much like one :). Am I right? >>> >>> Thanks for your help, >>> Barbara >>> >>> >>> On 27/08/2014 22:53, Christian Thode Larsen wrote: >>> >>>> Hi Barbara, >>>> >>>> I'm not aware of any way that you can do it directly by passing >>>> arguments to recon-all (some might correct me on that), but it is >>>> possible: >>>> >>>> 1) As N3 models the bias as a multiplicative effect uncorrected = >>>> corrected * bias, the simplest way is to divide each voxel of the volume >>>> before and after correction, in order to obtain a volume containing the >>>> bias. Note that N3 (by default) works within a mask where low-intensity >>>> voxels have been thresholded away. These voxels will contain garbage if >>>> you divide all voxels in the volume. >>>> >>>> 2) Somewhat more complicated: you can specify the -keeptmp flag combined >>>> with -tmp SOMEDIR/ (remember the trailing slash) to N3, in order to >>>> preserve its working files. This requires you to modify the N3 binary >>>> call in the mri_nu_correct.mni script. You also need to convert the mnc >>>> files from the tmp dir, so that you can work with the volumes. >>>> >>>> 3) if you do 2), you also get hold of the low-intensity voxel mask that >>>> N3 operates within. You can use this to constrain the division mentioned >>>> in 1). >>>> >>>> Best, >>>> Christian >>>> >>>> On 8/27/2014 11:18 PM, Barbara Kreilkamp wrote: >>>> >>>>> Dear all, >>>>> >>>>> Is there a way to output the N3's (non-parametric normalization step) >>>>> output? >>>>> I am interested in the bias field that was computed to correct the >>>>> image >>>>> intensities. >>>>> >>>>> Thank you for your help, >>>>> Barbara >>>>> _______________________________________________ >>>>> Freesurfer mailing list >>>>> Freesurfer(a)nmr.mgh.harvard.edu >>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>>> >>>>> >>>>> The information in this e-mail is intended only for the person to whom >>>>> it is >>>>> addressed. If you believe this e-mail was sent to you in error and the >>>>> e-mail >>>>> contains patient information, please contact the Partners Compliance >>>>> HelpLine at >>>>> http://www.partners.org/complianceline . If the e-mail was sent to >>>>> you in error >>>>> but does not contain patient information, please contact the sender >>>>> and properly >>>>> dispose of the e-mail. >>>>> >>>>> _______________________________________________ >>>> Freesurfer mailing list >>>> Freesurfer(a)nmr.mgh.harvard.edu >>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>> >>> _______________________________________________ >>> Freesurfer mailing list >>> Freesurfer(a)nmr.mgh.harvard.edu >>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>> >>> >>> >>> _______________________________________________ >> Freesurfer mailing list >> Freesurfer(a)nmr.mgh.harvard.edu >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >> > >

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Post-doctoral opportunity (and beyond) in neuroimaging analysis
by Willem Huijbers 29 Aug '14

29 Aug '14

PostDoc (or beyond) in Neuro Image Analysis: Magnetic Resonance Imaging – Code 1267/2014/8 Description: Population Health Sciences at the DZNE aims to investigate causes and preclinical biomarkers of neurodegenerative diseases, and to study normal and pathological brain structure and function over the adult life course. To this end we are currently establishing the Rhineland Study, a prospective population based cohort study that will include up to 30,000 people aged 30 years and over. The study facilities will encompass 3 dedicated examination centers equipped with state-of-the art 3T MRI scanners (Siemens Prisma), advanced bio-banking facilities and large data storage and computational clusters for analysis of big data.All study participants will undergo extensive phenotyping. This encompasses repeated and detailed brain imaging, including structural (T1, T2, T2*) and functional imaging (DTI, perfusion and BOLD imaging). A subset of the cohort will additionally be followed with 7T imaging and possibly PET imaging. We are looking for enthusiastic and ambitious researchers who will contribute to the further development of neuro image analysis in the framework of the Rhineland Study. The qualified applicant should have a PhD in neuro-image analysis, cognitive neuroscience, computer science or related field and a strong research background in large-scale neuroimage processing or population neuroimaging. Applicants should have experience with existing tools for large-scale analysis of neuroimaging data (e.g. with SPM, FSL, AFNI, etc.), relevant programming experience (e.g. with MATLAB, Python), and proficiency in mathematics and statistics (R, SPSS). Working experience in epidemiological research or large-scale clinical studies is highly desirable. Demonstrable interest in quantitative research, strong analytical skills, ability for independent and critical thinking, and excellent communication and writing skills in the English language are a prerequisite. Creative, highly motivated and team-oriented candidates who dare to take initiative and enjoy working in a fast-growing, dynamic research environment in an internationally oriented biomedical institution, are strongly encouraged to apply. We offer a scientific position with a long-term perspective. The position is initially limited to two years with the possibility of extension. For further information, please contact Prof Monique M.B. Breteler (rhinelandstudy(a)dzne.de) Also, feel free to contact me if you are interested or if you want more information Willem Huijbers

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Using FS v5.3 for group analysis with recon-all done with FS v5.0
by Matthieu Vanhoutte 29 Aug '14

29 Aug '14

Dear experts, I'd like to use Freesurfer v5.3 to make group analysis on quantitative CBF maps computed in volume and projected on fsaverage surface. Knowing that all my subjects have been recon-all with FS v5.0, is this neccesary to me to relaunch recona-all to all my subjects with FS v5.3 before I do my group analysis ? Precisely, until now I have only used from FS v5.0 : -> "T1.mgz" to register ASL on anatomical -> "mri_vol2surf" to project CBF maps on fsaverage surface and smooth them Thank you for replying ! Best, ------------------------------------- Matthieu Vanhoutte, MSc Research Engineer - Department of Neuroradiology Regional University Hospital, Lille, France

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recon-all fails with MCSRCH ERROR and tumors
by Joshua Goh 28 Aug '14

28 Aug '14

Dear FS List, I recently encountered a couple of issues with some patient data that caused recon-all not to work. Recon.log files attached. The first error seems to be during the EM alignment step and has an MCSRCH ERROR and applies to 1030813-1, 1030813-3, and P201503416. The T1s look generally fine except that there might be some WM degradation. But I’ve seen worse that worked. Is this because the brain is too far off the center for alignment to the GCA atlas? Would reorienting or manual centering here help? The second error applies to U200057992 and may be a segmentation problem. For this case, there is a tumor in the WM, along with WM degradation. Is Freesurfer able to handle WM tumors? Thanks! Josh

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recon-all fails with MCSRCH ERROR and tumors
by Joshua Goh 28 Aug '14

28 Aug '14

1 0

Output Time
by Isaiah C. Smith 28 Aug '14

28 Aug '14

Hello Experts, I was wondering if there is a way to short time of recon-all; I see that by using some of the parameters, one can get rid of different outputs. For mne forward models and inverses is there a recommended list of necessary and unnecessary outputs? Isaiah Smith

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Creating ROI
by Diaz Rodriguez, Juan 28 Aug '14

28 Aug '14

I am trying to create a spherical ROI mask in the form of a volume file with 2.5 cm radius. I also have to specify the center of the ROI location. What is the best way to accomplish this? I intend to use this to extract freesurfer cortical thickness values for a region-of-interest (ROI) defined in volume space as described in https://surfer.nmr.mgh.harvard.edu/fswiki/VolumeRoiCorticalThickness

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Freesurfer August 2014