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30132 discussions

Longitudinal errors, Voxel size differs
by Erik O'Hanlon 04 Jul '18

04 Jul '18

External Email - Use Caution Hi FS Experts, I'm trying to run a longitudinal analysis across three timepoints and have run the cross steps for the data. I then ran the base step but found that my voxel dimensions are slightly different across the timepoints and I got the following error ERROR: MultiRegistration::loadMovables: images have different voxel sizes. Currently not supported, maybe first make conform? Debug info: size(2) = 0.881117, 0.881117, 0.881117 size(0) = 0.884507, 0.884507, 0.884507 MultiRegistration::loadMovables: voxel size is different /projects/pi-vokeane/HPC_16_00925/MC_FS_testdata_EOH/freesurfer/subjects/abd025_tp3/mri/norm.mgz. I assume I need to resample the data to the voxel size of the first time point and then rerun. Can you advise on what command to use to resample the images from time 2 and time 3 to those of time 1 before rerunning from scratch. I assume I can't avoid rerunning the initial reconall step once I resample my data. Any guidance is much appreciated Best regards Erik Erik O'Hanlon Postdoctoral researcher [cid:rcsi-crest-signature_f581c185-1d03-45c8-a786-23d8ece3d391.png] RCSI Psychiatry Royal College of Surgeons in Ireland Beaumont Road, Beaumont D9 Ireland T: 8093740 E: erikohanlon(a)rcsi.ie W: www.rcsi.com<http://www.rcsi.com/> Transforming Healthcare Education, Research and Service: RCSI Strategic Plan 2018-2022<http://www.rcsi.ie/strategy2018> RCSI DEVELOPING HEALTHCARE LEADERS WHO MAKE A DIFFERENCE WORLDWIDE [cid:both3_b9da8717-e91f-4ea7-8729-dc2c4d0a7a5f.png]

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Longitudinal Process
by Samir Rekic 04 Jul '18

04 Jul '18

External Email - Use Caution Dear FreeSurfers, I am trying to run the longitudinal process including (recon-all -base and -long) for 5 different timepoints. But in my original data one the of five differs in the acquisition orientation and in the size of the field of view, so the results and especially the statistic is distorted. Four of my data sets have RPI as acquisition Parameter and a FOV of 230, the last data set has LPI and a FOV of 257. Does it even make sense to include this last dataset – is it even possible (due to different Parameters)? Do I have to pre-process this different data set? Thank you in advance! Sam

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"WARNING: Image geometries differ across time" upon running base step of longitudinal pipeline
by Tudor Popescu 04 Jul '18

04 Jul '18

External Email - Use Caution Dear all, I have pre and post-intervention data for a single group of subjects, and I'd like to extract the cortical thickness pre and post, for all standard regions in the atlas, and use those in subsequent analyses. Following the standard approach <https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalProcessing#Longitudin…>for longitudinal studies, I used the following types of commands: 1. *recon-all -i 01_1.nii.gz -subjid 01_1 recon-all -i 01_2.nii.gz -subjid 01_2 recon-all -i 02_1.nii.gz -subjid 02_1 .. where e.g. 01 is the subj code, and _1 and _2 represent pre and post scans* 2. *recon-all -subjid 01_1 -all recon-all -subjid 01_2 -all ..* 3. *recon-all -base 01 -tp 01_1 -tp 01_2 -all .. * 4. *recon-all -long 01_1 01 -all recon-all -long 01_2 01 -all .. * However, the base step has led to warnings of the type: "WARNING: Image geometries differ across time, maybe due to aquisition changes? This can potentially bias a longitudinal study! ", and consequently to an empty /stats folder -- even though my pre and post images are aligned and have similar acquisition parameters. Have I done something wrong, and how can I fix this warning/error? Many thanks in advance for any help. Best wishes, Tudor

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Geometries-related error from base step & absent norm.mgz
by Tudor Popescu 04 Jul '18

04 Jul '18

External Email - Use Caution Dear FS list, ( Apologies for asking my question again which I am still struggling to resolve and which I tried to clarify and condense below. ) I have pre and post-intervention data for a single group of subjects, and I'd like to extract the cortical thickness at both timepoints, for all standard regions in the atlas. I followed the standard approach <https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalProcessing#Longitudin…>for longitudinal studies, however the third ('base') step immediately gives this error: *"WARNING: Image geometries differ across time, maybe due to aquisition changes? This can potentially bias a longitudinal study! "* I don't think the acquisition parameters of the pre-post images actually differ: I could verify that all images indeed have - identical voxel size (1x1x1) - identical image size (176x224x160) - a (0,0,0) point that overlaps well-enough on the anterior commissure This suggests trivial (if any) "geometry" differences, and at Bruce's suggestion, I used mri_convert to resample each subject's 'post' to their 'pre' baseline: mri_convert -rl 01_1.nii.gz 01_2.nii.gz 01_2resampled.nii.gz (and renamed the resampled file to 01_2). However, the base step, recon-all -base 01 -tp 01_1 -tp 01_2 -all still gives the same error about geometries, and also in addition, this one: mghRead(/media/FS/01_1/mri/norm.mgz, -1): could not open file MultiRegistration::loadMovables: could not open input volume /media/FS/01_1/mri/norm.mgz. Inside /media/FS/01_1/mri/ (where /media/FS is my $SUBJECTS_DIR), there is indeed no norm.mgz, which suggests something in my previous commands for subject1: recon-all -i 01_1.nii.gz -subjid 01_1 recon-all -i 01_2.nii.gz -subjid 01_2 recon-all -subjid 01_1 -all recon-all -subjid 01_2 -all ..had gone wrong despite these having produced no errors. Although I thought the base step already does autorecon1 as part of the longitudinal pipeline, I tried doing it manually: recon-all -autorecon1 -subjid 01 however this returns: ERROR: It appears that this subject ID is an existing base/template from longitudinal processing (-base). Please make sure you pass all necessary flags. For example, if you are trying to re-run a -base: \' -base <templateid> -tp <tpNid> ... \' ..whereas running autorecon1 and 2 for the first *timepoint *instead, recon-all -autorecon1 -autorecon2 -subjid 01_1 returns mri_em_register: could not open input volume nu.mgz Should I in fact use, in mri_convert -rl , a *single *target for all the pre&post images in the study, like the study-specific template <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLVBM/UserGuide#C_-_Creating_the_te…> used by VBM? Or what else can I try to get the base step to continue? I'm very grateful for any suggestions! Cheers, Tudor

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mri_Coreg or bbregister
by John Anderson 03 Jul '18

03 Jul '18

External Email - Use Caution Dear Freesurfer experts, I have ten PET frames for every subject in my database. these frames represent specific time during PET acquisition. Due to head motion during acquisition the frames are not fully overlapped on top of each other. I created template represent the mean of the ten frames. I would like to register each low res frame to this low res template. Which tool in Freesurfer is more robust to achieve this goal. Any additional suggestions are highly appreciated Thanks John

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MRI2MESH Yielding Abnormal Volumes
by Palig Mouradian 03 Jul '18

03 Jul '18

External Email - Use Caution Hi Freesurfer, I am working on creating head models using the add-on mri2mesh command that incorporates free surfer. Once I have my mesh, I view it in SCIRUN to see how each surface was modeled. First time through, I noticed white matter abnormalities and that the nasopharynx was being included into the CSF. I did free surfer QC—edited the pial boundary and reran the mri2mesh command, I was successful in eliminating the WM abnormality but it has results in a ballooning of the CSF and skin surface (see attached). My main question is where can I attenuate this abnormality? Is it a result of my edits to the pial boundary? Thank You! Sincerely, Palig Mouradian

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mri_glmfit for first level ?
by Evelyn Eger 03 Jul '18

03 Jul '18

External Email - Use Caution Dear Freesurfer experts, I would like to know whether mri_glmfit can be used to estimate first-level (single subject) models as well or whether it is clearly not intended/recommended for that. I have noticed that it allows to specify a design matrix explicitly and I used the one previously configured in SPM, estimated the individual subject models on the surface and got reasonable results. Then after reading a bit more I gathered that this function is usually used for second-level analyses, and that my models are lacking the temporal autocorrelation correction and do not take into account additional drift terms as one would usually do. I noticed however that there is as well the possibility to compute and save the temporal AR1 with the --tar1 option, but I do not understand how this is taken into account afterwards. Would I get a proper first-level model by activating the --tar1 option and potentially adding additional drift terms to my design matrix myself, or would there be still remaining issues and the models should better be redone completely with selxavg3-sess (which seems a bit more complicated because the data were not organized in the required way from the start)? Thanks a lot in advance, Evelyn -- Dr Evelyn Eger INSERM Cognitive Neuroimaging Unit Neurospin - CEA Saclay F-91191 GIF/YVETTE, FRANCE Tél : 33 (0)1 69 08 19 06 Fax : 33 (0)1 69 08 79 73

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recon.all strange run time
by Ottavio Morciano 03 Jul '18

03 Jul '18

External Email - Use Caution Hi!I have a macbook pro MY 2014 with a Intel Core i7(quad core,2.7 ghz) and 16 gb of ram with El Capitan.This Macbook to run recon-all it takes 47 hours with -openmp 8 flag. A Dell with Intel Core i7 3632Q,8 GB RAM DDR3 1600mhz with Linux takes 8 hours...The same Dell on windows with linux virtualizated takes 13 hours. Why recon-all on mac is so slow? is the OS?the type of compilator used for each platform?freesurfer not optimized for El Capitan? the architecture of the cpu? Some Advice? Morciano Ottavio MD Student Università Di Foggia.Italy

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Problem with FreeSurfer
by Soan Duong 03 Jul '18

03 Jul '18

External Email - Use Caution Dear FreeSurfer, My name is Soan Duong. I used FreeSurfer to segmentation some high-resolution T1w images (resolution of 0.5x0.533x0.533, size of 288x378x420), and got a couple of problems: 1. I ran the command: recon-all -i DH_anat.nii -s DH -all, then got stuck with the error of Talairach failed!. I searched on the Internet and a guy suggested adding -notal-check flag in the command. I was successful with running recon-all -i DH_anat.nii -s DH -all -notal-check, but not understand about the added flag. 2. I ran recon-all with 3 T1w images of 3 subjects (with the same MP2RAGE sequence), the segmentation of a subject is weird (please see the image axial_245.png in the attachment). It seems to me that the left and right separation is not correct. Please noted that the other two segmentation is fine. I have attached the recon-all log files of the image with problem. 3. The segmentation results are down-resolution. Thus I tried to run recon-all with -hires flag: recon-all -i DH_anat.nii -s DH -all -hires -expert expert.opts -notal-check. The recon-all has been getting stuck with 'CORRECTING DEFECT 43 (vertices=65073, convex hull=7583, v0=36813' on the terminal screen for nearly one week. I have attached the used expert file. I am having trouble figuring out where these issues are coming from and how to solve them. I was wondering if you would have any ideas on what might going wrong/how to address it? Any help you have to offer would be greatly appreciated. Best regards, Soan --- Soan Duong PhD Candidate School of Electrical, Computer and Telecommunications Engineering Faculty of Engineering and Information Sciences University of Wollongong Northfields Avenue, Wollongong, NSW 2522, Australia

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Convert text file into surface file?
by Lukas Kunz 03 Jul '18

03 Jul '18

External Email - Use Caution Dear Freesurfers, is it possible to convert a text file (containing x/y/z-coordinates and corresponding values) into a Freesurfer surface file to display it on a standard volume (e.g., fsaverage)? Thanks in advance! Luke

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