FSL Evaluation and Example Data Suite To accompany FSL version 1.3 FMRIB Image Analysis Group, Oxford University

INTRODUCTION

This package performs two functions - it tests whether your FSL tools are working properly, and provides example data to try running FSL on.

The evaluation of FSL is carried out by a single script which normally takes between 1 and 3 hours to run (depending on your computer), testing every major tool in FSL on example data. It compares the output of each test with output data which is supplied with this package, and reports significant differences as failures.

The example data includes both example input and example output data. There is a detailed description below of how to analyse the input data - this is a quick way of starting to use FSL.

For up-to-date information regarding FSL see the FSL home page. For support relating to FSL or related theory, email the FSL email list or, even better, join the FSL email list.

DOWNLOADING THE FSL EVALUATION AND EXAMPLE DATA SUITE

If you have not already downloaded the FSL Evaluation and Example Data Suite then do so now.

Now unpack the distribution (it doesn't matter where you do this) by typing
gunzip fsl-feeds-1.3.tar.gz
tar xvf fsl-feeds-1.3.tar

RUNNING THE EVALUATION

• Make sure the FSLDIR environment variable points to the top level fsl directory. This might be, for example, /usr/local/fsl or /home/bart/fsl :
  • bash users: export FSLDIR=/usr/local/fsl; export PATH=$PATH:$FSLDIR/bin
  • tcsh users: setenv FSLDIR /usr/local/fsl; setenv PATH ${PATH}:$FSLDIR/bin; rehash
• cd into the top level directory feeds.
• Type time ./RUN
• (If you are interested in comparing how fast FSL runs on your computer with other computers, the final output - the time marked with a u - tells you how many CPU seconds or minutes the test took to run.)

The script RUN uses input data from the data subdirectory, and saved all output in the results subdirectory. It then compares this output with the test output data in the data subdirectory. (Note that test input and output data is mixed together in data, as in some cases the output from one tool was used as input to another one.) So - each tool's output is compared with the example data ouput and a percentage error is generated - this may not be exactly zero as different hardware platforms can give slightly different results without this being classified as an "error". Each tool's error is scaled so that a reported error of 1% is considered a failure.

If you get any failures, you may want to send us the complete text output from RUN, and also even the complete results directory.

USING THE EXAMPLE DATA TO LEARN FSL

INTRODUCTION

We now explain how the different tools in FSL can be run on the example data provided in the data subdirectory. We strongly suggest that you work with a copy of data rather than the original, so that you can always go back to the original data if you need to. You can do this by typing (inside feeds)
cp -r data examples
cd examples
and theh work with the files inside examples.

The instructions given below should produce the same output as provided in data.

Now make sure the FSLDIR environment variable points to the top level fsl directory. This might be, for example, /usr/local/fsl or /home/bart/fsl :

• bash users: export FSLDIR=/usr/local/fsl; export PATH=$PATH:$FSLDIR/bin
• tcsh users: setenv FSLDIR /usr/local/fsl; setenv PATH ${PATH}:$FSLDIR/bin; rehash

To start the main FSL GUI, type fsl.

To view the output of each tool, either load the output image(s) into your favourite Analyze image viewer (e.g. MEDx), or use the simple (non-interactive) display program slices which is in the fsl/bin directory (the setup commands above should have already placed this within your path). Where links appear below, these mostly point to 2D GIF images created by running slicer on the relevant Analyze format 3D image. (slicer is a command-line program which takes a 3D Analyze format image and produces a 2D GIF image with various slices at various orientations from the input image; slices is a script which calls slicer and then starts up a 2D image viewer to show you the GIF image.)

BET

SUSAN

FAST

FLIRT

FUGUE

SIENA

FEAT

• Press Select 4D data and select fmri.hdr.
• Press Full model setup to setup the GLM details.
• Change the Number of EVs to 2.
• Setup EV1 (the visual stimulation timing): set Off to 30, On to 30 and Phase to 30. This describes a square wave of total period 60s, starting with an ON period, hence the phase setting.
• Setup EV2 (the auditory stimulation timing): set Off to 45, On to 45 and Phase to 45. This describes a square wave of total period 90s, starting with an ON period, hence the phase setting.
• Now setup the Contrasts. Set the Number of contrasts to 2, set the first (C1) to [1 0] and the second (C2) to [0 1]. Thus the first output colour overlay image produced will show visual activation as only EV1 is used, and the second will show only auditory activation.
• Now setup the F-tests. Set the Number of F-tests to 1. Select both contrasts. Thus the third output colour overlay image produced will show where either visual or auditory activation occurs (i.e. will show both on a single image).
• Press Done to finish the model setup.
• Set the High pass filter cutoff to 100. Although it is common to set this to 1.5 times the maximum stimulation period (in this case 90*1.5=135), the nonlinear filter used in FEAT has quite a slow roll-off above the cutoff frequency, so in fact setting this to just over the 90s period time is fine.
• Press the triangle next to Advanced options, and press the button next to Registration. Note that the default settings in Pre-stats and Thresholding & rendering can be left as they are.
• In the Registration section, select the Subject's high resolution image. Set this to structural_brain.hdr.
• You are now ready to run FEAT. Press Go. As FEAT completes the different stages of processing, you will see messages appear on your terminal. When it has finished, the final messages will tell you the file name of a web page which you can view with your web browser to see the results.

MELODIC

Steve Smith
FMRIB Analysis Group
Copyright © 2000, University of Oxford