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[wiki:Self:FsTutorial top] [[FsTutorial|top]]
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== FreeSurfer Tutorial: Sample Data == == FreeSurfer Tutorial Datasets ==
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A [http://surfer.nmr.mgh.harvard.edu/pub/dist/buckner_public_distribution.README.txt public distribution data set] is available to run the tutorials. It contains 40+ subjects, and occupies about 11G of disk-space after download and uncompression. There are two download methods: using a web browser, or using the ftp application. The ftp application is recommended, as some web browsers have difficulty downloading files greater than 4GB in size. The data set for the Freesurfer tutorials comes in two forms, a "light weight" version and a "full" version.
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=== Download using the FTP application ===   * The "light weight" version contains only the files required to run the commands of the free surfer tutorial. It has all the required input and output data, but lacks the other subject data that would normally be present when performing a recon. People who just want a quick easy way to run the commands in the tutorial should download this data set.
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At your terminal, type '''ftp surfer.nmr.mgh.harvard.edu'''. Login as '''anonymous''' and use your email address as the password.   * The "full" version contains all the files that would normally be present when performing recons. Because of the numerous subjects involved with the tutorials, the full data set is quite large (~60Gigs). People who want to go into more depth than that which is covered in the course and the tutorials should download this data set.
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Example login: == FreeSurfer Tutorial Datasets - light weight version ==

Use the following link to download the light weight version of the tutorial data:

  [[ftp://surfer.nmr.mgh.harvard.edu/pub/data/tutorial_data.tar.gz|tutorial_data.tar.gz]]

Once the download is complete, uncompress the data file - this usually this can be done by simply double-clicking. To run the tutorials, simply source Freesurfer, then define an environment variable called '''TUTORIAL_DATA''' to the location of the uncompressed file. For example:
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$ ftp surfer.nmr.mgh.harvard.edu
Connected to surfer.nmr.mgh.harvard.edu (132.183.202.158).
220 surfer.nmr.mgh.harvard.edu FTP server (Version wu-2.6.2-15.7x.legacy) ready.
Name (surfer.nmr.mgh.harvard.edu:fsurfer): anonymous
331 Guest login ok, send your complete e-mail address as password.
Password:
230 Guest login ok, access restrictions apply.
Remote system type is UNIX.
Using binary mode to transfer files.
ftp>
$> <source freesurfer>
$> export TUTORIAL_DATA=/home/username/Downloads/tutorial_data
$> ls $TUTORIAL_DATA
buckner_data fsfast-functional
diffusion_recons fsfast-tutorial.subjects
diffusion_tutorial long-tutorial
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The tutorial datasets are found in the pub/dist directory: You are now ready to start the [[FsTutorial| Freesurfer tutorials]].

== FreeSurfer Tutorial Datasets - full version ==

The full data for the [[FsTutorial| tutorials]] consists of several data sets:
 * buckner_data-tutorial_subjs.tar.gz: the main 'recon-all' stream subject data processing (size: ~16GB uncompressed)[[ftp://surfer.nmr.mgh.harvard.edu/pub/data/buckner_data-tutorial_subjs.md5sum.txt|Here is the md5sum]].
 * long-tutorial.tar.gz: the longitudinal tutorial (size: ~16GB uncompressed)
 * fsfast-tutorial.subjects.tar.gz & fsfast-functional.tar.gz: the FS-FAST tutorial data set (size: ~5.6GB uncompressed & ~9.1GB uncompressed, respectively)
 * diffusion_recons.tar.gz & diffusion_tutorial.tar.gz - the diffusion and Tracula tutorial data sets
 * fbert-feat.tgz & bert.recon.tgz - tutorial on the integration of !FreeSurfer and FSL/FEAT

Also, if you only want to get started with the basics of !FreeSurfer, you need only download the buckner_data set. This will allow you to do the following tutorials:
 *[[FsTutorial/OutputData_freeview|Intro to FreeSurfer Output]]
 *[[FsTutorial/TroubleshootingData|Troubleshooting FreeSurfer Output]]
 *[[FsTutorial/GroupAnalysis|Group Analysis via command-line]]
 *[[FsTutorial/QdecGroupAnalysis_freeview|Group Analysis via GUI]]
 *[[FsTutorial/AnatomicalROI|ROI Analysis]]
 *[[FsTutorial/MultiModal_freeview|Multimodal Analysis]]

=== Download using wget ===
The wget application is recommended, as some web browsers have difficulty downloading files greater than 4GB in size. '''Mac OS NOTE:''' Use '''curl -O''' in place of '''wget'''.

Open a terminal, create a directory called {{{tutorial_data}}} where you know you have at least 100GB of space, and {{{cd}}} into that directory. To download, type:
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ftp> cd pub/dist wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/buckner_data-tutorial_subjs.tar.gz &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/long-tutorial.tar.gz &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/fsfast-functional.tar.gz &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/fsfast-tutorial.subjects.tar.gz &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/fbert-feat.tgz &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/bert.recon.tgz &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/diffusion_recons.tar.gz &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/diffusion_tutorial.tar.gz &
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The troubleshooting and group study analysis tutorials require the '''buckner_data-tutorial_subjs.tar.gz''' download, which is 6.5GB compressed (11GB uncompressed): This download will likely take several hours.

The wget application will handle poor connections, and retry if it is having problems. A failed download can be restarted by adding the -c flag to wget, which will cause it to continue from the point where a partial download stopped. Notice the commands have the ampersand, so you can run all these commands at once (although the wget output will be hard to decipher, so an alternative is to run each without the ampersand in a separate terminal). Go to the Installation section below once the files are downloaded.

==== Optional Verification Step ====
If you want to verify the files transferred correctly using md5sum, the md5sum for each of these downloads can found in files named *.md5sum.txt [[http://surfer.nmr.mgh.harvard.edu/pub/data/|in this directory]] or get them this way:
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ftp> get buckner_data-tutorial_subjs.tar.gz wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/buckner_data-tutorial_subjs.md5sum.txt &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/long-tutorial.md5sum.txt &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/fsfast-functional.md5sum.txt &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/fsfast-tutorial.subjects.md5sum.txt &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/fbert-feat.md5sum.txt &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/bert.recon.md5sum.txt &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/diffusion_recons.md5sum.txt &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/diffusion_tutorial.md5sum.txt &
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Now exit the ftp application: You will want to ensure that these md5sum's match what you find when you run md5sum on your own local downloads. If they do not match, the file transfer may have been faulty or there may have been a disk error. '''Mac OS NOTE:''' Use '''md5 -r''' to get the same results as '''md5sum'''. More on md5sum can be found [[http://www.techradar.com/us/news/computing/pc/how-to-verify-your-files-in-linux-with-md5-641436|here]].

=== Installation ===
==== Uncompress the files ====
Once the dataset(s) have been downloaded, uncompress and install with the following command run from a terminal window.
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ftp> quit tar xzvf <filename>.tar.gz
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=== Download using the web browser ===
Some web browsers seem to have difficulty downloading files greater than 4GB in size, but if you would like to attempt the download using your browser, then the one necessary file is listed next (click on the .tar.gz filename to download).
Replacing <filename> with the name of the file downloaded. The downloaded .tar.gz files can then be deleted.
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The troubleshooting and group study analysis tutorials require this download:
 * [ftp://surfer.nmr.mgh.harvard.edu/pub/dist/buckner_data-tutorial_subjs.tar.gz buckner_data-tutorial_subjs.tar.gz]
==== Set variables to point FreeSurfer to data ====
To setup the environment variable {{{SUBJECTS_DIR}}} to point to the tutorial data, type the following commands every time you open a new terminal window. Alternatively, you can include the below commands in your .cshrc or .tcshrc file so these variables are automatically set every time you open a new terminal window:
{{{
(bash)
export TUTORIAL_DATA=<absolute_path_to_tutorial_data_directory>
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=== Installation ===

Once the file is downloaded (via either ftp or web browser), move the file(s) to the $FREESURFER_HOME/subjects directory, and uncompress and install with the following command:

{{{
tar xzvf buckner_data-tutorial_subjs.tar.gz
(csh)
setenv TUTORIAL_DATA <absolute_path_to_tutorial_data_directory>
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The downloaded .tar.gz file can then be deleted. '''Note:''' The tutorial references the {{{TUTORIAL_DATA}}} variable, which is the root directory containing the tutorial data (ie. the directories 'buckner_data', 'long-tutorial', 'fsfast-functional', etc.).
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To setup the environment variable SUBJECTS_DIR to point to the tutorial data, type the following command or include in your .cshrc or .tcshrc file: === FSL-FEAT Tutorial Data ===
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source $FREESURFER_HOME/subjects/buckner_data/tutorial_subjs/scripts/subjects.csh cd $SUBJECTS_DIR
tar xvfz bert.recon.tgz
cd /place/for/functional/data
tar xvfz fbert-feat.tgz
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The tutorial will also instruct you to set the SUBJECTS_DIR when appropriate.

=== Additional group study data ===
There is an additional data set available upon which further group study analysis could be conducted. It is composed of the 40 subjects from which the tutorial's group study component was created. The data set is the full Freesurfer reconstruction of the 40 subjects (conducted using stable v3.0.2). It is 10.5GB compressed, and 18GB uncompressed. It is named '''buckner_data-group_study.tar.gz'''. Also, there is the file '''buckner_data-raw_dicoms.tar.gz''', which, as indicated by the name, contains the original DICOM files for the subjects. Be sure to [http://surfer.nmr.mgh.harvard.edu/pub/dist/buckner_public_distribution.README.txt read these notes.]

top

FreeSurfer Tutorial Datasets

The data set for the Freesurfer tutorials comes in two forms, a "light weight" version and a "full" version.

  • The "light weight" version contains only the files required to run the commands of the free surfer tutorial. It has all the required input and output data, but lacks the other subject data that would normally be present when performing a recon. People who just want a quick easy way to run the commands in the tutorial should download this data set.
  • The "full" version contains all the files that would normally be present when performing recons. Because of the numerous subjects involved with the tutorials, the full data set is quite large (~60Gigs). People who want to go into more depth than that which is covered in the course and the tutorials should download this data set.

FreeSurfer Tutorial Datasets - light weight version

Use the following link to download the light weight version of the tutorial data:

Once the download is complete, uncompress the data file - this usually this can be done by simply double-clicking. To run the tutorials, simply source Freesurfer, then define an environment variable called TUTORIAL_DATA to the location of the uncompressed file. For example:

$> <source freesurfer>
$> export TUTORIAL_DATA=/home/username/Downloads/tutorial_data
$> ls $TUTORIAL_DATA 
buckner_data                    fsfast-functional
diffusion_recons                fsfast-tutorial.subjects
diffusion_tutorial              long-tutorial

You are now ready to start the Freesurfer tutorials.

FreeSurfer Tutorial Datasets - full version

The full data for the tutorials consists of several data sets:

  • buckner_data-tutorial_subjs.tar.gz: the main 'recon-all' stream subject data processing (size: ~16GB uncompressed)Here is the md5sum.

  • long-tutorial.tar.gz: the longitudinal tutorial (size: ~16GB uncompressed)
  • fsfast-tutorial.subjects.tar.gz & fsfast-functional.tar.gz: the FS-FAST tutorial data set (size: ~5.6GB uncompressed & ~9.1GB uncompressed, respectively)

  • diffusion_recons.tar.gz & diffusion_tutorial.tar.gz - the diffusion and Tracula tutorial data sets

  • fbert-feat.tgz & bert.recon.tgz - tutorial on the integration of FreeSurfer and FSL/FEAT

Also, if you only want to get started with the basics of FreeSurfer, you need only download the buckner_data set. This will allow you to do the following tutorials:

Download using wget

The wget application is recommended, as some web browsers have difficulty downloading files greater than 4GB in size. Mac OS NOTE: Use curl -O in place of wget.

Open a terminal, create a directory called tutorial_data where you know you have at least 100GB of space, and cd into that directory. To download, type:

wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/buckner_data-tutorial_subjs.tar.gz &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/long-tutorial.tar.gz &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/fsfast-functional.tar.gz &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/fsfast-tutorial.subjects.tar.gz &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/fbert-feat.tgz &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/bert.recon.tgz &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/diffusion_recons.tar.gz &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/diffusion_tutorial.tar.gz &

This download will likely take several hours.

The wget application will handle poor connections, and retry if it is having problems. A failed download can be restarted by adding the -c flag to wget, which will cause it to continue from the point where a partial download stopped. Notice the commands have the ampersand, so you can run all these commands at once (although the wget output will be hard to decipher, so an alternative is to run each without the ampersand in a separate terminal). Go to the Installation section below once the files are downloaded.

Optional Verification Step

If you want to verify the files transferred correctly using md5sum, the md5sum for each of these downloads can found in files named *.md5sum.txt in this directory or get them this way:

wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/buckner_data-tutorial_subjs.md5sum.txt &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/long-tutorial.md5sum.txt &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/fsfast-functional.md5sum.txt &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/fsfast-tutorial.subjects.md5sum.txt &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/fbert-feat.md5sum.txt &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/bert.recon.md5sum.txt &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/diffusion_recons.md5sum.txt &
wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/diffusion_tutorial.md5sum.txt &

You will want to ensure that these md5sum's match what you find when you run md5sum on your own local downloads. If they do not match, the file transfer may have been faulty or there may have been a disk error. Mac OS NOTE: Use md5 -r to get the same results as md5sum. More on md5sum can be found here.

Installation

Uncompress the files

Once the dataset(s) have been downloaded, uncompress and install with the following command run from a terminal window.

tar xzvf <filename>.tar.gz

Replacing <filename> with the name of the file downloaded. The downloaded .tar.gz files can then be deleted.

Set variables to point FreeSurfer to data

To setup the environment variable SUBJECTS_DIR to point to the tutorial data, type the following commands every time you open a new terminal window. Alternatively, you can include the below commands in your .cshrc or .tcshrc file so these variables are automatically set every time you open a new terminal window:

(bash)
export TUTORIAL_DATA=<absolute_path_to_tutorial_data_directory>

(csh)
setenv TUTORIAL_DATA <absolute_path_to_tutorial_data_directory>

Note: The tutorial references the TUTORIAL_DATA variable, which is the root directory containing the tutorial data (ie. the directories 'buckner_data', 'long-tutorial', 'fsfast-functional', etc.).

FSL-FEAT Tutorial Data

cd $SUBJECTS_DIR
tar xvfz bert.recon.tgz
cd /place/for/functional/data
tar xvfz fbert-feat.tgz

FsTutorial/Data (last edited 2018-09-30 09:35:54 by AndrewHoopes)