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| 1. Creation of computerized models of the brain from magnetic resonance imaging (MRI) data [RECON link here] | 1. Creation of computerized models of the brain from magnetic resonance imaging (MRI) data. [wiki:Self:FsTutorial/MorphAndRecon link] |
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| 2. Processing of functional magnetic resonance imaging (fMRI) data [FSFAST link here] | 2. Processing of functional magnetic resonance imaging (fMRI) data. [wiki:Self:FsFastTutorial link] |
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| 3. Measuring a number of morphometric properties of the brain including cortical thickness and regional volumes [THICKNESS wiki link] | 3. Measuring a number of morphometric properties of the brain including cortical thickness and regional volumes [THICKNESS wiki link] |
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| 4. Intersubject averaging of structural and functional using a procedure that aligns individuals based on their cortical folding patterns for optimal alignment of homologous neural regions [SPHERICAL wiki link] | 4. Intersubject averaging of structural and functional using a procedure that aligns individuals based on their cortical folding patterns for optimal alignment of homologous neural regions [SPHERICAL wiki link] |
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| To run Freesurfer, you will need either a PC running Linux or a Macintosh running OSX (OPTIMAL MACHINE wiki link- I think even a linke quote for a machine woud be best). |
To run Freesurfer, you will need either a PC running Linux or a Macintosh running OSX (OPTIMAL MACHINE wiki link). |
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| The processing procedures for the creation of cortical models requires good quality T1 weighted MRI data, such as a Siemens MPRAGE ([http://www.nmr.mgh.harvard.edu/~andre/: examples of appropriate Siemens scanner protocols])or GE SPGR sequence with approximately 1mm^3 resolution (although a variety of quality datasets can be processed with additional manual intervention). |
The processing procedures for the creation of cortical models requires good quality T1 weighted MRI data, such as a Siemens MPRAGE ([http://www.nmr.mgh.harvard.edu/~andre/: examples of appropriate Siemens scanner protocols])or GE SPGR sequence with approximately 1mm^3^ resolution (although a variety of quality datasets can be processed with additional manual intervention). '''Getting Started''' There is a variety of documentation about the use of Freesurfer contained in the Freesurfer wiki including [wiki:Self:DownloadAndInstall installation of the software], [wiki:Self:FsTutorial tutorials], [wiki:Self:FsTutorial/Data sample data], and [wiki:Self:WorkFlows work flows] providing step by step guides to performing specific tasks. To get started, we suggest you: 1. Install Freesurfer [wiki:Self:DownloadAndInstall click here] 2. Download the sample dataset [wiki:Self:FsTutorial/Data click here] 3. Follow the cortical reconstruction tutorial to create cortical models [wiki:Self:FsTutorial click here] 4. Peruse the wiki to get a fuller knowledge of all of the available processing procedures in the Freesurfer software package An active [wiki:Self:FreeSurferSupport e-mail list] is available to answer specific questions about processing procedures. |
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'''Data Requirements: MRI Parameters''' FreeSurfer requires that the MRI data conform to certain parameters. The slice thickness should be 1.3mm and the Field of View should be 256mm. To see examples of appropriate Siemens scanner protocols, refer to: http://www.nmr.mgh.harvard.edu/~andre/ For best results, each subject should have at least one sagittal structural scan. These scans are averaged and automatically corrected for motion before further processing. |
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'''Work Flows''' Consult the WorkFlows section to learn the detailed workings of a FreeSurfer processing stream. |
FreeSurfer Beginners Guide
FreeSurfer is a freely available software package developed by investigators at the [http://www.nmr.mgh.harvard.edu: Athinoula A. Martinos Center for Biomedical Imaging] used for a number of procedures including:
Creation of computerized models of the brain from magnetic resonance imaging (MRI) data. [wiki:FsTutorial/MorphAndRecon link]
Processing of functional magnetic resonance imaging (fMRI) data. [wiki:FsFastTutorial link]
- Measuring a number of morphometric properties of the brain including cortical thickness and regional volumes [THICKNESS wiki link]
- Intersubject averaging of structural and functional using a procedure that aligns individuals based on their cortical folding patterns for optimal alignment of homologous neural regions [SPHERICAL wiki link]
Machine Requirements
- To run Freesurfer, you will need either a PC running Linux or a Macintosh running OSX (OPTIMAL MACHINE wiki link).
Data Requirements
The processing procedures for the creation of cortical models requires good quality T1 weighted MRI data, such as a Siemens MPRAGE ([http://www.nmr.mgh.harvard.edu/~andre/: examples of appropriate Siemens scanner protocols])or GE SPGR sequence with approximately 1mm3 resolution (although a variety of quality datasets can be processed with additional manual intervention).
Getting Started
There is a variety of documentation about the use of Freesurfer contained in the Freesurfer wiki including [wiki:DownloadAndInstall installation of the software], [wiki:FsTutorial tutorials], [wiki:FsTutorial/Data sample data], and [wiki:WorkFlows work flows] providing step by step guides to performing specific tasks. To get started, we suggest you:
Install Freesurfer [wiki:DownloadAndInstall click here]
Download the sample dataset [wiki:FsTutorial/Data click here]
Follow the cortical reconstruction tutorial to create cortical models [wiki:FsTutorial click here]
- Peruse the wiki to get a fuller knowledge of all of the available processing procedures in the Freesurfer software package
An active [wiki:FreeSurferSupport e-mail list] is available to answer specific questions about processing procedures.
TO DOWNLOAD THE SOFTWARE: [wiki:DownloadAndInstall follow this link]
Overview
An overview of the major processing steps taking place in a standard FreeSurfer workflow are described in this PDF slide presentation: [http://surfer.nmr.mgh.harvard.edu/docs/ftp/pub/docs/FSL_anatomical_stream.pdf Building Anatomical Models with Freesurfer].
See also: FreeSurferAnalysisPipelineOverview
The end result: FreeSurfer will produce a single, high quality 3D structural volume, corresponding 2D surfaces, and automatically segmented subcortical structures for each of your subjects. You can also use FreeSurfer to generate an average subject out of all the participants in your study, upon which you can display individual subject data -- structural and/or functional -- thus making FreeSurfer a practical option for individual and group analyses.