FSL Evaluation and Example Data Suite

FEEDS for FSL v4.1

intro   -   download   -   running the evaluation   -   timing results   -   using example data

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, 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.tar.gz
tar xvf fsl-*-feeds.tar


RUNNING THE EVALUATION

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 then work with the files inside examples.

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

Make sure your environment is setup correctly for using FSL - see the Running section on the Downloading and Installing page.

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, 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

Set the Input image to be structural and press OK. The output will be structural_brain. You will see a message on your terminal when BET has finished.



SUSAN

Set the Input image to be structural. Set the Brightness threshold to 2000 (this is greater than the noise level and less than the grey-white contrast in the input image). Set the Mask SD to 2 (this sets the mask half-width to be 2mm). Press OK. The output will be structural_susan.



FAST

Set the Input image to be structural_brain (i.e. it is important to have run BET first). Turn on the Partial volume maps optional output images. Press Go. The outputs will be structural_brain_seg, structural_brain_pve_0, structural_brain_pve_1 and structural_brain_pve_2.



FLIRT

Set the Input image to be structural_brain. Set the Output image to be structural_brain2standard. Press Go.



FUGUE

FUGUE does not have a GUI. On the command line type
prelude -c fieldmap -u unwrapped_phase
This runs the phase map unwrapping. Now type
fugue -i epi -p unwrapped_phase -d 0.295 -u unwarped_epi
This runs the unwarping of the input epi image.



SIENAX

SIENAX does not have a GUI. On the command line type
sienax structural
This runs the SIENAX cross-sectional (single-time-point) atrophy script, producing a web-page report structural_sienax/report.html.



FEAT



MELODIC

Set the 4D input data to be fmri. Note that this is the same raw data as was input to FEAT - normally you would ideally want to have done some pre-processing to the data before running MELODIC - see the MELODIC help page for more information on this. Press Go. When MELODIC 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.

FIRST

First you must register your data to standard space; in a terminal type
first_flirt structural structural_to_std_sub
Now run a single structure's segmentation; type
run_first -i structural -t structural_to_std_sub.mat -n 20 -o structural_first_L_Hipp -m \
    ${FSLDIR}/data/first/models_317_bin/L_Hipp_bin.bmv



FDT

To reconstruct the example data, open the FDT GUI and change the top option to BEDPOSTX: Estimation of diffusion parameters. Select the input directory fdt_subj1 and pres Go. To load some of the output images into FSLView, type
cd fdt_subj1.bedpostX
fslview nodif_brain mean_f1samples dyads1

then press the (i) near the bottom of FSLView, to bring up the Overlay Information Dialog. Make sure dyads is highlighted in the overlay list, and change the Display as to RGB. Change the Modulation to mean_f1samples (this is similar to the fractional anisotropy). You can now see colour-coding of the principal diffusion direction vector. Now change the Display as to Lines to see the same vectors represented as small red lines.



Steve Smith
FMRIB Analysis Group
Copyright © 2000-2007, University of Oxford