Hi Sair, Just to make sure, could you run? fspython -m pip install nibabel Otherwise you can re-install the distribution as we have update the latest one with the missing nibabel package. Best, Lilla ________________________________ From: Carlos Sair Flores Bautista sairfb@inb.unam.mx Sent: Wednesday, February 10, 2021 8:52 PM To: Zollei, Lilla,Ph.D. LZOLLEI@mgh.harvard.edu Cc: freesurfer@nmr.mgh.harvard.edu freesurfer@nmr.mgh.harvard.edu Subject: Missed Module nibabel Python -- Re: Form submission from: Infant Freesurfer Download Request

External Email - Use Caution

Hello Freesurfer Team

My Name is Sair, i have been trying to run a test subject on last dev version of freesurfer infant pipeline, however when i try to run this subject i receive the next error from infant recon all process:

Reslicing using trilinear interpolation writing to /home/lain/Documents/PruebasFsInfant/test/work/mprage.nu.conf.nii.gz... CONFORMED FILE /home/lain/Documents/PruebasFsInfant/test/work/mprage.nu.conf.nii.gz Traceback (most recent call last): File "/usr/local/freesurferinfant/python/scripts/sscnn_skullstrip", line 5, in <module> import nibabel as nib ModuleNotFoundError: No module named 'nibabel'

it suppose the last freesurfer infant dev version contains python 3.6 however i have made sure to check the availability of this module on the installed python version however this still happens every time, also i have made the same test on different server and pc getting the same error. i have tested it on debian and ubuntu

I have attached to this mail the complete stream from my infant recon all test in order to analyze and help to receive support from your side.

thanks in advance.

Best regards

Sair.

L.C.E. Carlos Sair Flores Bautista Secretario Tecnico INB-UNAM

El mié, 13 de ene. de 2021 a la(s) 15:24, Zollei, Lilla,Ph.D. (LZOLLEI@mgh.harvard.edumailto:LZOLLEI@mgh.harvard.edu) escribió: Thank you for your interest in the infantFreesurfer pipeline. The version below is our new beta distribution (Jan 2021). Please, continue giving me feedback and asking a lot of questions along the way so that we can improve upon the user-friendliness of its use.

After downloading the package, you should run the below four commands:

source YOUR_FREESURFER_ENVIRONMENT setenv SUBJECTS_DIR your_data_path or export SUBJECTS_DIR=your_data_path infant_recon_all --s SUBJ --age age_in_months

SUBJ is the subjectID of the subjects's whose data you are processing. The script will expect the input file to be located at $SUBJECTS_DIR/$subj/mprage.nii.gz or $SUBJECTS_DIR/ $subj/mprage.mgz by default. Unless otherwise specified, the output of this process will be saved to $SUBJECTS_DIR/$SUBJ using a FreeSurfer type directory structure. If the --masked flag is used, we recommend also running intensity normalization, for example by using: mri_nu_correct.mni --i $infile --o $nufile --n 2

Note, you can use both tcsh and bash for this distribution.

Before execution, you will also need install FSL [https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FslInstallationhttps://secure-web.cisco.com/1cGp1eiz_7sOm02QhOvn3jmhR4tJTNPCAhjpNXJy9K5rBP9D9YNX2T8lJQcyhwYwYEO3DMPtMGIsyfQ4IQZejMMCximy56W3k3ogi8f4aMgZoSenWjT6eRaKvBExtIsTcnt3qpV2UiKJ_Q0uokLmCXJR5EKlMzwsApkwyJgxlNyUUjUvvxVzSmVU0TWLWW6vpbXO7VR7UUP7D8JrOZ-11zPbZikv3oFK942XrdZfARuE9bYcPYuL3wO8WQfqXnGWnqlq43jjvtqTl-SLJsYKE-Q/https%3A%2F%2Ffsl.fmrib.ox.ac.uk%2Ffsl%2Ffslwiki%2FFslInstallation]. Note, we have changed our default nonlinear registration tool. We rely on niftyreg which ships directly with this release. If you would like to use DRAMMS you will need to install it separately and use the corresponding flag.

Other useful flags: --outdir (redirecting output) --kneigh (number of training examples to use) See infant_recon_all --help for more information or visit https://surfer.nmr.mgh.harvard.edu/fswiki/infantFShttps://secure-web.cisco.com/1SO4Xs7x3V6qnRb_RWiJBY343GLDSD6_eDDvRSlrhuC-wTqsvcFEEES4dfnqSbk7cKGEfnRgUQGDR4ssoqwKEqGlfaYZIEmC9taOPQeRnGfK9ZTx4xkiF8d9laXZfKauHrIcvvSayfXrgGCs_3HEwksu-N8QGEnEqxfOhiHr7YIWlYt115eoohXJCZDEPLXy5Rd52hRvVaRPsbKErRE-zosHUOlHhksIRPGZn8wg9KhH68HfTPfIB1FCOKhX7LSAMtpQrBjL4EdVcaDgdn33MTQ/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FinfantFS

* Skullstripping

The current release ships with our new skullstripping tool so you will not need to skullstrip your data before running infantFS. Note, the new tool requires about 23GB of memory! At present, the error messages related to lack of sufficient memory are pretty vague, so please, check whether you have enough if you rely on this tool. Also "Your CPU supports instructions that this TensorFlow binary was not compiled to use" is just a warning not an error. It indicates that the process could be faster if you built with a more modern tensorflow, but the computations should be working even with this version.

* Citation: Cite the below papers if you use our work and publish yourself:

Zöllei, L, Iglesias, JE, Ou, Y, Grant, PR, Fischl,B. Infant FreeSurfer: An automated segmentation and surface extraction pipeline for T1-weighted neuroimaging data of infants 0-2 years, NeuroImage, Volume 218, September 2020, 116946 https://doi.org/10.1016/j.neuroimage.2020.116946https://secure-web.cisco.com/1QyTKPVjpukeljrh0n5fRo7K-S_AxdepVjCQ_yydZp7OgYPzMqYmphRMmidVUTFRqvJXms9ppbsAtyV3RRCD4qWZQUXC560ltXAB-HbHjPzwne4pQKejd62hJhBsouHLXNxvEOwqD7QUvmNGR2y1JlyiP1s2XD_DObDAff4Am2OmnW0WFNFBRkcA3q4v0cfd9Hah6NVnoj4vytKumETGWKv9tKryHsSHEdR3ntmMniiBhPTrEYuXpPQ7qEF2DUY3c11gL-6nEsrRZfeOEE2hSxA/https%3A%2F%2Fdoi.org%2F10.1016%2Fj.neuroimage.2020.116946. (http://www.sciencedirect.com/science/article/pii/S1053811920304328http://secure-web.cisco.com/124O1IxeSlJOGHpA_Mg0Tx1tyLZSHjY4vKxlkhb2cRAzqZwBobJF_tyUjKlD0IxTtbQ49GOtVwaVUCW-Sj4sDLZ6EWxhDFFUm6FgOEYDnmw24R2FgkLtyIH1FGQdskaK8o8Coj7SpFHW0zYXrJ2Vj-uScqxnEmr5jEkpNtO0vtCvd0Iv4tCL0-K7jEtj9ayEw2guWt5anHcEsNILdBp6AEA45HLupvh3ezWJxUujJGPzz9-76LrlYiVBfpjwD6PYmpncR91XMwlegDne08P1WWw/http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS1053811920304328)

de Macedo Rodrigues, K., et al., A FreeSurfer-compliant consistent manual segmentation of infant brains spanning the 0–2 year age range. Front. Hum. Neurosci., 2015. 9(21).

* Download:

https://surfer.nmr.mgh.harvard.edu/ftp/dist/freesurfer/infant/freesurfer-lin...https://secure-web.cisco.com/1tBEYaGAdDitkfPUajg7pJGKaxxzO-KQ7FVRcE-R55wnSj3kr2HnTgI8K9Fkk5VoVIYOTAoUNt7AweCZpgd80Yad73dbAhgkiyHYah_HD8iWf2VJqsFefuHbZBaIybnauo7lM8vN67A0Wy0FjCaLJklQP80I0iq0zyOH90PEwOkW17Sz-uH0BYe5vsUkdBvh424LB993LyHaHMru6K4-0u2kU18iXeRN9MzmFX_Prtr_UrT8-mT7m9Gq8vRtECIu4TlU7aLZzhoBwXUbqx7-c6w/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Fftp%2Fdist%2Ffreesurfer%2Finfant%2Ffreesurfer-linux-centos7_x86_64-infant-dev-4a14499.tar.gz

Lilla

NOTE: Currently, the parcellation information (aparc) is provided only for the sake of completeness but has not been fully validated. It is a projected version of the adult atlas, so it does not originate from the infant training data set directly!

________________________________ From: webmaster@nmr.mgh.harvard.edumailto:webmaster@nmr.mgh.harvard.edu <webmaster@nmr.mgh.harvard.edumailto:webmaster@nmr.mgh.harvard.edu> on behalf of MGH/HST Martinos Center for Biomedical Imaging via MGH/HST Martinos Center for Biomedical Imaging <webmaster@nmr.mgh.harvard.edumailto:webmaster@nmr.mgh.harvard.edu> Sent: Thursday, January 7, 2021 10:12 AM To: lzollei@nmr.mgh.harvard.edumailto:lzollei@nmr.mgh.harvard.edu <lzollei@nmr.mgh.harvard.edumailto:lzollei@nmr.mgh.harvard.edu> Subject: Form submission from: Infant Freesurfer Download Request

Submitted on Thursday, January 7, 2021 - 10:12 Submitted by anonymous user: 189.128.48.80 Submitted values are:

Name: Carlos Sair Flores Bautista Email Address: sairfb@inb.unam.mxmailto:sairfb@inb.unam.mx Institution: UNAM-México Operating System Used: Debian Intended use of the Pipeline: analyze the neurodevelopment between perinatal brain damage subject dataset and control subject data set during 0-8 years in a longitudinal analysis

The results of this submission may be viewed at: https://www.nmr.mgh.harvard.edu/node/8319/submission/31809https://secure-web.cisco.com/1ZLBHTi_QZ1M8KoGgrzKvLFWXqE6-zLjpsABpjUgPA4ubTQkUxA1PxpGn2lJ8h885z6NJ4ffeognurnP46NDc0DwWDWTWFzYg8jlPX7XMv5jKj8mVGMt6hVS88Bzxmgq52fN16fPW7yJiVZroK1iCGtDL9xwyZcszKjXEnCS4u-8qnvsE45lduwc8TUeDCLpdCOsA2dl52WDiPOVZL1JuHGvxGp6l6JxafcOuU6yOFft26ZQOajOCfIrpX2w2JPN0HNJPos6bhwN3PUauK2NQhg/https%3A%2F%2Fwww.nmr.mgh.harvard.edu%2Fnode%2F8319%2Fsubmission%2F31809

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