FreeSurfer is a set of automated tools for reconstruction of the brain’s cortical surface from structural MRI data, and overlay of functional MRI data onto the reconstructed surface.

FreeSurfer is a set of automated tools for reconstruction of the brain’s cortical surface from structural MRI data, and overlay of functional MRI data onto the reconstructed surface.

http://surfer.nmr.mgh.harvard.edu/

FreeSurfer is brought to you by the Athinoula A. Martinos Center for Biomedical Imaging. Support for this research was provided in part by the National Center for Research Resources (P41-RR14075, R01 RR16594-01A1 and the NCRR BIRN Morphometric Project BIRN002, U24 RR021382), the National Institute for Neurological Disorders and Stroke (R01 NS052585-01), the National Institute of Biomedical Imaging and Bioengineering, as well as the Mental Illness and Neuroscience Discovery (MIND) Institute and is part of the National Alliance for Medical Image Computing (NA-MIC) funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149.

http://www.google.com/codesearch/p?hl=fr&sa=N&cd=1&ct=rc#voO8-N1ttR0/mesh_freesurfer2emse.m&q=MRI%20mesh%20matlab

FreeSurfer Beginners Guide

http://surfer.nmr.mgh.harvard.edu/fswiki/FreeSurferBeginnersGuide

FreeSurfer is a freely available software package developed by investigators at the Athinoula A. Martinos Center for Biomedical Imaging used for a number of procedures including:

  1. Creation of computerized models of the brain from magnetic resonance imaging (MRI) data. link
  2. Processing of functional magnetic resonance imaging (fMRI) data. link
  3. Measuring a number of morphometric properties of the brain including cortical thickness and regional volumes. link
  4. Intersubject averaging of structural and functional data using a procedure that aligns individuals based on their cortical folding patterns for optimal alignment of homologous neural regions. link

Machine Requirements

To run FreeSurfer, you will need either a PC running Linux or a Macintosh running OS X.

FreeSurfer consumes a lot of processor time, memory resources and disk space, so it is recommended to run FreeSurfer on as powerful a machine as you have available. For example, at MGH we typically run Linux CentOS 4 on 2.5GHz dual processor AMD Opterons with 4 to 8 GB of DDR SDRAM, and 250GB of disk space.

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The FreeSurfer tools deal with two main types of data: volumetric data (volumes of voxels) and surface data (polygons that tile a surface). The talks and tutorials should familiarize you with FreeSurfer’s volume and surface processing streams, the recommended workflow to execute these, and many of their component tools. The tutorials also describe some of FreeSurfer’s tools for registering volumetric datasets, performing group analysis on morphology data, and integrating multi-modal output with FreeSurfer (overlaying color coded parametric maps onto the cortical surface and visualizing plotted results). After completing the tutorials, you should be able to:

  • perform surface reconstructions;
  • generate subcortical segmentations;
  • fix errors encountered during the volume or surface processing;
  • overlay functional data onto surfaces;
  • perform group analysis of structural (e.g. thickness) and functional data.

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