Freesurfer August 2016

freesurfer@nmr.mgh.harvard.edu

127 participants
198 discussions

Flattening the surface
by Younghoon Kim 09 Sep '16

09 Sep '16

Hello, We have a volumetric data (mgz file) of a segmented brain region. We want to detect the surface of this segmented brain volume (i.e. deep brain region) and flatten it into a 2D image with its original surface texture. We’ve noticed that Freesurfer supports an algorithm to flatten volumetric data. We wonder if this could be adapted to our data set. Can anyone offer some advice on how to apply FreeSurfer to this more generic task? Thanks, Younghoon Kim -- Younghoon Kim, Dep. of Bio and Brain Engineering, KAIST OMICS Lab Wellman Center, Massachusetts General Hospital Bouma’s Lab ---------------------------------------------- younghoon.h.kim(a)gmail.com aktivhoon(a)kaist.ac.kr

2 14

when to -qcache in longitudinal processing
by Linette Savage 06 Sep '16

06 Sep '16

Hello Freesurfers, My ultimate goal is a MLE analysis of 2 groups (n~25) at 2 time points. I have followed the longitudinal processing stream (cross, base, long) although only ran -qcache at the cross stage. Do I need to add this flag to the base and/or long recon-all command? Or is the same thing achieved by running this code (described in the LME wiki page under Preparing your data): mris_preproc --qdec-long long.qdec.table.dat --target fsaverage --hemi lh --meas thickness --out lh.thickness.stack.mgh mri_surf2surf --hemi lh --s fsaverage --sval lh.thickness.stack.mgh --tval lh.thickness.stack.fwhm10.mgh --fwhm-trg 10 --cortex --noreshape I'm using Freesurferv5.3.0 on OS X El Capitan although about to move to a Linux system. Thanks kindly, Linette Savage University of Calgary Brain Training Study www.braintrainingstudy.ca<http://www.braintrainingstudy.ca>

2 1

white matter errors due to inhomogeneities (bright spots) in cortex
by Benjamin Baird 01 Sep '16

01 Sep '16

Dear Freesurfer experts, We are currently working with some scans that were collected on a GE 3T scanner. The goal is to analyze cortical thickness. The scans seem to be relatively high quality with the exception that there are what appear to be inhomogeneities in the intensity of the gray matter (appears too bright in places), which is causing the WM to extend/jump into cortex (see attached image). We're wondering if there are any parameter adjustments to recon that might help with this as the errors occur frequently enough that fixing them all manually will be fairly cumbersome. This type of error doesn’t seem to be discussed very much in the available information on freesurfer quality control as far as we’ve seen. Thanks in advance for any thoughts recommendations or advice you might be able to offer. Best regards, Ben

2 1

bigventricles, inaccurate segmentation
by Carol Nguyen 01 Sep '16

01 Sep '16

Hello FreeSurfer Developers, I am attempting to segment a brain with large ventricles. I was able to create a decent brainmask.mgz but the aseg segmentation after running autorecon2 and autorecon3 is neglecting a part of one hemisphere (see a picture attached). I tried to readjust the talairach parameters with tkregister without success. Running autorecon2 with "-bigventricles" flag did yield a similar result as running without it. Lastly, for your information, I use FS v5.3. I am also attaching the recon-all.log from the most recent attempt. Can you please advise me how to get the correct segmentation of such a brain? Thank you! Best regards, Carol *Carol Nguyen* University of Minnesota, Twin Cities Researcher | Department of Pediatrics Division of Neuropsychology nguy1903(a)umn.edu

2 1

Pial refinement with FLAIR
by Eelco van Duinkerken 01 Sep '16

01 Sep '16

Dear all, Sorry for spamming, as I have posted this message about 2 weeks ago, but didn't receive an answer just yet. I probably did something wrong :). I've been preprocessing, in FS5.3, 3T GE data in controls, obese and diabetes patients and adding the available flair to do the pial refinement as follows: recon-all -i t1 -s participant -all -FLAIR flair -FLAIRpial This works excellent for most of the scans. Unfortunately, for some scans adding the flair leads to some interesting refinements, either extending outside of the brain.mgz or going deep into the white matter. I didn't notice any misregistrations of the flair to the T1 scan when checking the bb-registration. I have added some screenshots and the recon-all.log files. The red lines represent the pial with the flair refinement, and the blue lines the pial without the refinement. As you can see, these interesting segmentations are not there when the flair is no used. Does anyone know what is going on? Thanks a lot, Eelco -- Eelco van Duinkerken, PhD Pontifícia Universidade Católica | Department of Psychology | R. Marquês de São Vicente 225 | Gávea, Rio de Janeiro - RJ | CEP 22451-900 | Brasil | E-mail: e.vanduinkerken(a)vumc.nl | Phone: +55-21-35271855 | http://lattes.cnpq.br/7180895567820901 & VU University Medical Center | Department of Medical Psychology | De Boelelaan 1117 | 1081 HV | Amsterdam | The Netherlands

3 3

inclusion of both T1 and T2 in a recon-all run
by Krieger, Donald N. 01 Sep '16

01 Sep '16

Dear list: What are the advantages of including a T2 scan when running recon-all -all ? Which results can it effect and to what extent? And how sensitive is freesurfer to artifacts in the T2 scan? Is there a good reference for this/ Thanks and best - Don

5 8

3 fixed factors and matrix design
by Shady Rahayel 01 Sep '16

01 Sep '16

Greetings, I want to design a matrix that contains 3 fixed factors. The first is diagnosis (3 levels), the second is gender (2 levels), and the last is imaging site (2 levels). However, the thing is that the imaging site factor only applies to only one level of the diagnosis factor (i.e. patients from the first level of the diagnosis factor were seen in 2 different imaging sites, whereas for the two other groups of patients the same imaging site was used). I have followed the tutorials but I still be am confused concerning how I should go about creating the design matrix with 3 fixed factors. Would it be: GroupDescriptorFile 1 Title xx Class Diagnosis1-Male-Site1 Class Diagnosis1-Female-Site1 Class Diagnosis1-Male-Site2 Class Diagnosis1-Female-Site2 Class Diagnosis2-Male-Site1 Class Diagnosis2-Female-Site1 Class Diagnosis3-Male-Site1 Class Diagnosis3-Female-Site1 Input etc etc... Afterwards, if I'm looking for a difference between Diagnosis1 and Diagnosis2, what would be the contrast? 0.25 0.25 0.25 0.25 -0.5 0.5 0 0 ? Thank you very much for your help, Shady -- *Shady Rahayel* Étudiant au Ph.D. en neuropsychologie R/I Université du Québec à Montréal Centre d'Études Avancées en Médecine du Sommeil Hôpital du Sacré-Coeur de Montréal

2 1

mri_glmfit: Cannot allocate memory
by Heidi Foo 01 Sep '16

01 Sep '16

Dear FreeSurfer team, I tried to run glm_fit to fit group membership. For this model, I have 3 diagnostic groups namely, HC, MCI, AD, and added lobar (Frontal, Parietal, Occipital, Temporal) WMH as the covariates. My contrasts are as follow: Group membership: 1 -1 0 0 0 0 0 0 0 0 0 0 0 0 0; 0 1 -1 0 0 0 0 0 0 0 0 0 0 0 0 Frontal/Parietal/Occipital/Temporal MCI_HC: 0 0 0 -1 1 0 0 0 0 0 0 0 0 0 0 Frontal/Parietal/Occipital/Temporal MCI_AD: 0 0 0 -1 1 0 0 0 0 0 0 0 0 0 0 Frontal/Parietal/Occipital/Temporal AD_HC: 0 0 0 -1 0 1 0 0 0 0 0 0 0 0 0 However, I got the error message that matlab element type is not a matrix and another error that it cannot allocate memory. Attached the error log and the command for your reference. I am not sure what went wrong, any help will be great. Many thanks, Heidi

1 1

About TRACULA results
by Kang, XJ 31 Aug '16

31 Aug '16

Hi, I am trying to computer the changes of cortical parcellations and fiber pathways using FreeSurfer v5.3 and Tracula (2014/05/26 update) . I copied the anatomical and DWI images from the same scan session into five directories. Run recon-all and trac-all on the 5 same data sets, in order to check thereproducibility of the analysis. Here are what I got: the /Desikan/-Killiany parcellations in both GM and WM, and the subcortical structures, repeat well. No difference found in volume or size of those structures. However, the volume and averaged DTI parameters of the fiber pathways, which found in the file ~/sub/dpath/*_PP_avg33_mni_flt/pathstats.overall.txt, varies for the 5 sets. tracula.conf files were copied from ~/freesurfer/bin/dmrirc.example. The changes are calculated in percentage by (S1-S0)/((S1+S0)/2)*100%. For example, the changes of averaged FA between the 5 data sets are : S1-S0, S2-S0, S3-S0, S4-S0 Corpus Callosum - Forceps Major , -1.1 , 6.0 , 0.5 , 1.3 , Corpus Callosum - Forceps Minor , 0.1 , 0.0 , -1.6 , 0.0 , Right Anterior Thalamic Radiations , 0.1 , -1.0 , 0.5 , 0.9 , Right Cingulum - Angular Bundle , -4.8 , -2.0 , -1.5 , 3.8 , Right Cingulum - Cingulate Gyrus Endings , 0.5 , -0.9 , 0.4 , -2.3 , Right Corticospinal Tract , 1.9 , 0.6 , -2.2 , 1.4 , Right Inferior Longitudinal Fasciculus , -2.2 , -0.8 , -1.3 , 3.0 , Right Superior Longitudinal Fasciculus - Parietal Endings , 0.8 , -0.4 , -1.2 , 0.2 , Right Superior Longitudinal Fasciculus - Temporal Endings , -4.9 , -0.6 , -2.6 , -1.3 , Right Uncinate Fasciculus , 0.5 , 1.6 , -0.9 , 3.5 , Even larger changes for the volume of the pathways: S1-S0, S2-S0, S3-S0, S4-S0 Corpus Callosum - Forceps Major , 2.2 , -33.7 , -12.3 , 1.1 , Corpus Callosum - Forceps Minor , 11.9 , 4.8 , 0.6 , 7.2 , Right Anterior Thalamic Radiations , -8.9 , 2.2 , -12.5 , 7.5 , Right Cingulum - Angular Bundle , -38.1 , 41.6 , 34.8 , 8.6 , Right Cingulum - Cingulate Gyrus Endings , 24.4 , 33.1 , 21.3 , 17.5 , Right Corticospinal Tract , 9.8 , -3.0 , 2.2 , 19.5 , Right Inferior Longitudinal Fasciculus , 7.2 , 24.1 , -7.3 , 23.8 , Right Superior Longitudinal Fasciculus - Parietal Endings , 17.2 , 10.2 , 25.1 , 9.9 , Right Superior Longitudinal Fasciculus - Temporal Endings , 15.4 , 3.4 , -3.1 , -11.5 , Right Uncinate Fasciculus , 13.3 , -1.2 , 16.4 , -3.4 , Any expert has the experience on these? Thank you for your help. XJ Kang

2 2

Satellite Symposia - Resting-State and Brain Connectivity Conference
by Anastasia Yendiki 31 Aug '16

31 Aug '16

Dear FreeSurfers - If you're attending the Resting-State and Brain Connectivity Conference in Vienna, you can now register for satellite symposia, including one on diffusion MRI. Hope to see you there! a.y ---------- We are pleased to inform you that registration for the six Satellite Symposia at the Resting-State and Brain Connectivity Conference is open! These specialised meetings will take place on Saturday, September 24th right after the Resting-State and Brain Connectivity Conference. So why not extend your stay in Vienna for the sake of maximizing knowledge gain, deepening the vivid scientific exchange and socializing with your community members? The Satellite Symposia will will cover diffusion MRI, optogenetics, PET/MRI, TMS/fMRI and predictive analyses of neuroimaging data. We made sure to provide a large selection of topics for our six Satellite Symposia, so that everyone gets to choose the most interesting on their behalf: * Symposium #1: Probing white-matter anatomy and microstructure with diffusion MRI * Symposium #2: Tackling connectivity using non-invasive brain stimulation (fMRI/TMS, tDCS, tACS) * Symposium #3: The Emerging Field of Predictive Analytics in Neuroimaging: Applications, Challenges and Perspectives * Symposium #4: Multi-modal fMRI from photons to protons * Symposium #5: Dynamic Functional Connectivity * Symposium #6: Network-Based Approaches for Neuroimaging: Graph Theory Techniques for Brain Connectivity Research http://www.restingstate.com/2016/satellite-symposia/ So don’t hesitate to register for a satellite symposium now! We look forward to welcoming you to Vienna in September 2016! On behalf of the local and international organizing committees Christian Windischberger Claus Lamm Rupert Lanzenberger Bharat Biswal Mark Lowe Christopher Pawela Martin Walter Susan Whitfield-Gabrieli

1 0

Jump to page:

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

Freesurfer August 2016