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30083 discussions

Confusion about discrete variable in the FSGD file
by Thalhammer, Melissa 08 Nov '21

08 Nov '21

External Email - Use Caution Dear FreeSurfer users, I am interested in cortical thickness differences between preterm (PT) and fullterm (FT) individuals. I have used DODS with mri_glmfit and wanted to regress out scanner (4 sites) and sex in the analysis, using the attached FSGD file. Both of the variables are discrete and I have found different information on how to include discrete variables into the model. I have followed Andrew Jahn's blog at first who includes discrete variables in the variable list just as continuous ones and specifies them with values of 0 or 1 (https://secure-web.cisco.com/1mCX947TtGflWAdnM3CtHlWXx5Aa4vkeu9B25dEdIVjquj…) I have adapted this procedure and have specified my gender values as 1 and 2 (simply because it was stated like this in the participants information sheet I have received). Recently, I have read a post on the mail archive, where Doug states: "you should not code gender and handedness as a continuous variables. In doing this, you are saying that you expect right handers to have 2x the thickness as left handers (or females to have 2x the thickness as males)" (https://secure-web.cisco.com/1A4RpPVoEFVSno401uhBm0BawiKw27S9-5VpEg7YyqN3rI…) When following this argument, this would also hold for continuous variables, i.e., a patient aged 50 would have 2x the thickness of a patient aged 25. So my question is how to correctly deal with discrete variables and why you have suggested to code gender as classes instead of variables. What is the actual difference? How does the model treat classes and variables? Cheers and many thanks in advance, Melissa Thalhammer

2 2

adding covariates to a longitudinal glmfit model
by Zeng, Qi 08 Nov '21

08 Nov '21

External Email - Use Caution Hi Experts, After completing long_mris_slopes to get the rate of change and then concatenating them into one.mgh file for group analysis (mris_preproc). I am finally getting to mris_glmfit. Got a couple of questions along the way. 1). if I conducted long_mris_slopes, and got for example, lh.long.thickness-rate.fwhm10.fsaverage.mgh. Do I need to do a surface smoothing again (mri_surf2surf) before mris_glmfit? 2). I construct covariates in FSGD besides the group contrast that I am interested in. How do I add covariates into the glmfit model to control for the covariates as I contrast groups in terms of the rate of changing (CV vs. NCV groups) . Do I add them into --C as (1, -1, 0(age), 0(gender), 0(race)). mri_glmfit --y {$hemi}.{$meas}-rate.{$smoothness}.mgh --fsgd FSGD/{$study}.fsgd doss --C Contrasts/CV-NCV.mtx (1, -1) --C Contrasts/NCV-CV.mtx (-1, 1) --surf fsaverage {$hemi} --cortex --glmdir {$hemi}.{$meas}-rate.{$study}.{$smoothness}.glmdir Best, Zeno --

2 2

tksurfer
by Arian Klows 08 Nov '21

08 Nov '21

External Email - Use Caution Hi experts, I recently downloaded the freesurfer and am testing it. I tried tksurfer, but the editor window is blank. Please see below. Can anyone please help me in resolving this issue!? [image: image.png] Is this an internal problem with my computer? If anyone knows an alternative way to visualize the window, please let me know. Thanks, A

3 2

Again: Confusion about discrete variable in the FSGD file
by Thalhammer, Melissa 08 Nov '21

08 Nov '21

External Email - Use Caution Dear FreeSurfer users, I am not sure whether my question was posted, so I will just ask it again. I am interested in cortical thickness differences between preterm (PT) and fullterm (FT) individuals. I have used DODS with mri_glmfit and wanted to regress out scanner (4 sites) and sex in the analysis, using the attached FSGD file. Both of the variables are discrete and I have found different information on how to include discrete variables into the model. I have followed Andrew Jahn's blog at first who includes discrete variables in the variable list just as continuous ones and specifies them with values of 0 or 1 (https://secure-web.cisco.com/1mCX947TtGflWAdnM3CtHlWXx5Aa4vkeu9B25dEdIVjquj…) I have adapted this procedure and have specified my gender values as 1 and 2 (simply because it was stated like this in the participants information sheet I have received). Recently, I have read a post on the mail archive, where Doug states: "you should not code gender and handedness as a continuous variables. In doing this, you are saying that you expect right handers to have 2x the thickness as left handers (or females to have 2x the thickness as males)" (https://secure-web.cisco.com/1A4RpPVoEFVSno401uhBm0BawiKw27S9-5VpEg7YyqN3rI…) When following this argument, this would also hold for continuous variables, i.e., a patient aged 50 would have 2x the thickness of a patient aged 25. So my question is how to correctly deal with discrete variables and why you have suggested to code gender as classes instead of variables. What is the actual difference? How does the model treat classes and variables? Cheers and many thanks in advance, Melissa Thalhammer

1 0

crash
by Nikolai Chapochnikov 06 Nov '21

06 Nov '21

External Email - Use Caution Hello, I just installed freesurfer 7.2.0 on mac os 11.6 using the pkg. Freeview opens, but as soon as I select a nii file to load, it crashes. Here is the report I get: https://secure-web.cisco.com/1S_Xfvu-lNCy7GOzAyxCVPdF0cy5djt33DYm0S7sznuCGb… Could someone please help with this? Thank you very much! Nikolai

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Splitting Yeo volume atlas to left and right components
by Paul Dhami 05 Nov '21

05 Nov '21

External Email - Use Caution Dear Freesurfer community, I have the 7-network Yeo atlas in MNI space and as a nifti file as downloaded from the Freesurfer website. Right now, the atlas has 7 labels for each of the networks. I however want to split this to the left and right hemisphere, ultimately creating 14 labels in a nifti file. Could anyone share as to if and how this can be done with Freesurfer (I am unsure due to it being in volume and not surface space)? Thank you.

2 1

FLIRT: Unexpected behaviour for DOF 3 (or 6) MB
by Mathieu Boudreau 04 Nov '21

04 Nov '21

External Email - Use Caution Hi, I was in the process of improving a pipeline running on the UKBB dataset, and encountered an unexpected behaviour that may be a bug or need clarifications. Situation: We have a ~40k dataset where our pipeline was failing for ~6k subjects, likely due to our FLIRT call hitting a local minima during registration (brains were misoriented after the call). flirt -ref "${mni_ref_brain}" -in "${IMG_brain}" -out "${T1_atlas}" -omat "${s2raff}" As you can see, our original call used the default DOF, which is 12. So, I explored using a second/pre FLIRT call using a reduced DOF in order to re-orient the brain to a better starting position prior to using the default12 DOF call. I tried doing so with 6, where I saw significant improvements (something like 80-90% of the failing pipeline subjects were then registering correctly). Then, just because, I tried it with DOF 3, and saw an even better improvement (something like 97-98% of subjects now working correctly), despite 1) me knowing that DOF 3 doesn't make sense for a 3D sample and 2) FLIRT throwing me an error stating this, and saying it was going to change it back to DOF 6. This is a bit annoying for me, because I'd expect that if an incorrect call to DOF 3 is changed to DOF 6 correctly, then both calls should produce the same behaviour. Instead, I'm getting an improvement by using DOF 3 rather than 6, even though that doesn't make sense if the exception handling was done correctly. But I also kinda wouldn't want it (3->6) be done correctly if it means I'll get the lesser performance that I'm seeing with DOF 6. I looked a little bit in the code, and could see from where the DOF 3->6 is handled (which is after setting the variables for both the 3 and 6 cases) how there might be some inconsistencies, but haven't really dug deep to see what exactly the difference would be. I'm happy to provide more information as needed. Here is my final call, which is providing me the best result (note that I also added a different cost function, but that was for my own additional improvements). flirt -ref "${mni_ref_brain}" -in "${IMG_brain}" -omat "${rough_affine}" -dof 3 -cost normcorr flirt -ref "${mni_ref_brain}" -in "${IMG_brain}" -out "${T1_atlas}" -omat "${s2raff}" -init "${rough_affine}" Best regards, Mathieu -- Mathieu Boudreau, PhD Research Fellow | Montreal Heart Institute Software Developer | qMRLab and AxonDeepSeg Lead Editor | MRM Highlights<http://secure-web.cisco.com/1S3wMWDASJrA3h1upfshg0SY8osuDC46MdU2zveoOoZr0J4…><https://secure-web.cisco.com/1O86gV8JQYi2w82a0_gCfL0dY9GYpFSjUCCtW5hMvluCDs…>

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FW: Faculty opening in ECE at University of Michigan in Image Analysis
by Fischl, Bruce 04 Nov '21

04 Nov '21

FYI -----Original Message----- From: Jeff Fessler <fessler(a)umich.edu> Sent: Thursday, November 4, 2021 8:56 PM Cc: fessler(a)umich.edu Subject: Faculty opening in ECE at University of Michigan in Image Analysis External Email - Use Caution Dear Colleague, This year, the Electrical and Computer Engineering Division of the EECS Department at the University of Michigan has an open faculty position in the field of Medical Image Analysis, broadly defined, along with several other related areas of interest (including signal processing, machine learning, data science and neurotech). Please encourage your outstanding doctoral students and postdocs to apply for one of these positions. Applicants at the Assistant Professor level should apply through our website: https://secure-web.cisco.com/1YmcmMARPB6bquPoAuPra973c3LqaHLXKWQMgGHX7GsOhs…. We are interested in considering applicants at all levels (Assistant through full Professor). Michigan has leaders in imaging and image formation in the College of Engineering and we intend to hire an expert in image analysis to complement existing strengths. Anyone at the mid-career or senior level who might be interested (possibly including yourself) should please feel free to contact us directly for a conversation. The Biomedical Engineering (BME) department at Michigan also has open faculty positions this year and one of their areas of special interest is artificial intelligence and machine learning. BME and ECE have successfully worked together to recruit faculty recently and are interested in coordinating the recruiting of applicants whose research and/or teaching interests might span both departments. For BME applications, see https://secure-web.cisco.com/1IfCZEcALKOHdddTZ7BqsYq2hIyYYoOaaf-drc1XcoLazC…. Applicants could apply to both units, or put a note in their cover letter to one unit expressing interest in also being considered in the other. The UM Medical Center, located less than 2 miles from the engineering campus, is an exceptionally strong research unit with extensive collaborations with College of Engineering faculty. In addition, many faculty in the sciences and other engineering departments have research programs involving imaging, from microscopic scales to astronomical scales, providing numerous opportunities for image analysis collaborations. We would especially welcome applications from individuals who would add diversity to our faculty. The application web portal will close in February 2021, though applications will be considered in the order received. Submitting before the end of December is preferable. Sincerely, Jeff Fessler, Member ECE Executive Committee fessler(a)umich.edu William L Root Professor of EECS (he/him/his) http://secure-web.cisco.com/1H8L3iEU_mGzgkEEeFHofJGjFmbVeAw2ACfs4scGjRQmDWp…

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PETsurfer
by Brusaferri, Ludovica 03 Nov '21

03 Nov '21

Hi! I have been using freesurfer regularly and I am now trying to implement a few commands from PETsurfer https://surfer.nmr.mgh.harvard.edu/fswiki/PetSurfer <https://surfer.nmr.mgh.harvard.edu/fswiki/PetSurfer>. It seems like I cannot use any of the commands listed in the wiki (such as gtmseg or mri_coreg), although they should be part of the freesurfer package (as PETsurfer is part of freesurfer). Do I need to follow a specific pipeline to install the PETsurfer extension? If so, could you please guide me through? Thanks so much in advance! Kindly, Ludovica

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Senior Research Assistant/Lab Manager position
by Illapani, Venkata Sita Priyanka (Priyanka) 03 Nov '21

03 Nov '21

External Email - Use Caution The Center for Prevention of Neurodevelopmental Disorders (CPND) at Cincinnati Children's Hospital Medical Center is recruiting Senior Research Assistant/Lab Manager with interest and experience in diffusion and functional brain MRI data acquisition and processing using connectometric approaches for neonates at high-risk for neurodevelopmental disorders. We have collected such data in more than 500 very preterm infants soon after birth and are currently collecting neurodevelopmental data up to 7 years of age. This is a great opportunity to contribute to additional high-quality MRI data collection, processing, data analysis, student mentoring, and manuscript writing. There will also be ample opportunities to learn new skills. Qualifications: * A Master's degree in Computer Science, Statistics, Physics, Engineering, Psychology, or related field with minimum 3 years of experience is required. * Experience with scripting/programming languages (MATLAB, Python, R, etc.) * Familiarity with MRI data analysis (fMRI, dMRI, qMRI, etc.) * Strong interpersonal and organizational skills * Familiarity with multimodal data analyses and modeling, advanced machine learning techniques, multivariate statistics and cloud computing is a plus. To apply: Please send your CV and a cover letter with names and contact information for three references to Nehal Parikh, DO, MS at nehal.parikh(a)cchmc.org More information about the lab: The NIH-funded research in the Parikh Lab within the CPND crosses multiple disciplines including computational neuroscience, multimodal neuroimaging, prognostication, and neurodevelopmental rehabilitation. Our focus is on integrating multimodal neuroimaging with advanced computational and engineering techniques to enable early diagnosis/prognosis and prevention of neurodevelopmental disorders. Cincinnati is a great Midwestern city with a dynamic downtown, restaurants, sports scene, and family values while Cincinnati Children's consistently ranks as one of the best places to work.

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