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[wiki:Self:FreeSurferWiki top]
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                                                                                 1. Creation of computerized models of the brain from magnetic resonance imaging (MRI) data [RECON link here]
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2. Processing of functional magnetic resonance imaging (fMRI) data [FSFAST 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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3. Measuring a number of morphometric properties of the brain including cortical thickness and regional volumes [THICKNESS wiki link]         2. Processing of functional magnetic resonance imaging (fMRI) data. [wiki:Self:FsFastTutorial 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]         3. Measuring a number of morphometric properties of the brain including cortical thickness and regional volumes. [https://surfer.nmr.mgh.harvard.edu/ftp/articles/fischl00-cortical-thickness.pdf 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. [https://surfer.nmr.mgh.harvard.edu/ftp/articles/fischl99-morphing.pdf 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 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 w/ 4 to 8GB of DDR SDRAM, and 250GB of disk space.

        See SystemRequirements for more info.
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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). The best Freesurfer processing results come from scans having excellent gray/white matter contrast.

        [attachment:example_scans.tif Examples of different quality scans (click to download TIFF image):]

            * '''A''' - excellent GM/WM contrast, acquired with MP-RAGE pulse-sequence protocol
            * '''B''' - very good GM/WM contrast, acquired with MP-RAGE pulse-sequence protocol
            * '''C''' - good GM/WM contrast, acquired with SPGR pulse-sequence protocol; not as good GM/WM contrast as the MP-RAGE acquisitions; low bandwidth causes some temporal lobe artifacts (brightening of the gray matter)

        These example scans, captured from Freesurfer's tkmedit display, are slices from the brainmask.mgz file, created by the -autorecon1 stage of Freesurfer (requiring about 20 minutes of processing time). This means that some amount of intensity normalization has occurred, but the contrast differences between image examples are easier to see, compared to the original (orig.mgz) volume. Refer the tutorial section's [wiki:Self:FsTutorial/ControlPoints 'Using Control Points to Fix Intensity Normalization'] and [wiki:Self:FsTutorial/WhiteMatterEdits 'Fixing Common Geometric Inaccuracies in White Matter Surfaces'] for examples of problem areas resulting from scan deficiencies.

'''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. Read the introductory material on Freesurfer from past lectures: [attachment:FSL_anatomical_stream.pdf slides (BF)] and [attachment:surferfest3.pdf slides (DG)]

            2. Read the background material: [wiki:Self:ArticlesSlidesAndPosters click here]

            3. Install Freesurfer: [wiki:Self:DownloadAndInstall click here]

            4. Download the sample dataset: [wiki:Self:FsTutorial/Data click here]

            5. Follow the cortical reconstruction tutorial to create cortical models: [wiki:Self:FsTutorial click here]

            6. Peruse the wiki to get a fuller knowledge of all of the available processing procedures in the Freesurfer software package
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'''''TO DOWNLOAD THE SOFTWARE:''''' [wiki:Self: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

'''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.

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.

'''Work Flows'''

Consult the WorkFlows section to learn the detailed workings of a FreeSurfer processing stream.




 An active [wiki:Self:FreeSurferSupport e-mail list] is available to answer specific questions about processing procedures.

[wiki:FreeSurferWiki top]

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:

  1. Creation of computerized models of the brain from magnetic resonance imaging (MRI) data. [wiki:FsTutorial/MorphAndRecon link]

  2. Processing of functional magnetic resonance imaging (fMRI) data. [wiki:FsFastTutorial link]

  3. Measuring a number of morphometric properties of the brain including cortical thickness and regional volumes. [https://surfer.nmr.mgh.harvard.edu/ftp/articles/fischl00-cortical-thickness.pdf 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. [https://surfer.nmr.mgh.harvard.edu/ftp/articles/fischl99-morphing.pdf 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 w/ 4 to 8GB of DDR SDRAM, and 250GB of disk space.

    See SystemRequirements for more info.

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). The best Freesurfer processing results come from scans having excellent gray/white matter contrast. [attachment:example_scans.tif Examples of different quality scans (click to download TIFF image):]

    • A - excellent GM/WM contrast, acquired with MP-RAGE pulse-sequence protocol

    • B - very good GM/WM contrast, acquired with MP-RAGE pulse-sequence protocol

    • C - good GM/WM contrast, acquired with SPGR pulse-sequence protocol; not as good GM/WM contrast as the MP-RAGE acquisitions; low bandwidth causes some temporal lobe artifacts (brightening of the gray matter)

    These example scans, captured from Freesurfer's tkmedit display, are slices from the brainmask.mgz file, created by the -autorecon1 stage of Freesurfer (requiring about 20 minutes of processing time). This means that some amount of intensity normalization has occurred, but the contrast differences between image examples are easier to see, compared to the original (orig.mgz) volume. Refer the tutorial section's [wiki:FsTutorial/ControlPoints 'Using Control Points to Fix Intensity Normalization'] and [wiki:FsTutorial/WhiteMatterEdits 'Fixing Common Geometric Inaccuracies in White Matter Surfaces'] for examples of problem areas resulting from scan deficiencies.

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:

    1. Read the introductory material on Freesurfer from past lectures: [attachment:FSL_anatomical_stream.pdf slides (BF)] and [attachment:surferfest3.pdf slides (DG)]

    2. Read the background material: [wiki:ArticlesSlidesAndPosters click here]

    3. Install Freesurfer: [wiki:DownloadAndInstall click here]

    4. Download the sample dataset: [wiki:FsTutorial/Data click here]

    5. Follow the cortical reconstruction tutorial to create cortical models: [wiki:FsTutorial click here]

    6. 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.

FreeSurferBeginnersGuide (last edited 2020-04-10 10:31:15 by LeahMorgan)