FSL

# Using FLIRT to Register a Few FMRI Slices |

## INTRODUCTION

If you need to take an FMRI data set where you only have a few slices (ie the field-of-view - FOV - is small in Z) then it is very hard to get a good registration with either the subject's structural or directly to a standard space image. This page describes our recommendations in such cases.

- Take your FMRI data, with only a few slices. We will refer to an example volume from this time series as example_func.
- Take a single whole-brain "functional" image (let's call this whole_func). This will normally be the same kind of image as example_func (eg EPI), but will cover the whole brain. It should contain, as a subset of its slices, the same slices as in example_func. In general there should be no rotation between func and whole_func.
- Now (optionally) take a high-resolution structural image, e.g. T1-weighted (let's call this highres).
- Finally, identify your standard space image (let's call this standard).

Now you are ready to register these all together.

## REGISTRATION

- First, register example_func to whole_func:
  flirt -ref whole_func -in example_func -schedule ${FSLDIR}/etc/flirtsch/ztransonly.sch \
  -out example_func2whole_func -omat example_func2whole_func.mat
  The custom FLIRT schedule file ztransonly.sch allows only translations in Z (in order for the registration to be robust), so there must be no rotation or within-slice translation between these images.
- Now register whole_func to highres:
  flirt -ref highres -in whole_func -out whole_func2highres -omat whole_func2highres.mat
- Now register highres to standard:
  flirt -ref standard -in highres -out highres2standard -omat highres2standard.mat
- Now combine the transforms:
  convert_xfm -concat whole_func2highres.mat -omat example_func2highres.mat example_func2whole_func.mat
  convert_xfm -concat highres2standard.mat -omat example_func2standard.mat example_func2highres.mat
- Now you could use these to transform stats images (eg produced by FEAT) in the space of the original func data into standard space:
  flirt -ref standard -in thresh_zstat1 -applyxfm -init example_func2standard.mat -out thresh_zstat12standard

## USING WITH FEAT

If you want to put these transforms into a FEAT directory so that running group stats with FEAT will work well, then do the following (instead of using the simple default registration carried out by FEAT):

- Run a first level FEAT analysis without registration - this creates an output FEAT directory.
- Place in your FEAT directory appropriate images called whole_func.hdr/.img, highres.hdr/.img and standard.hdr/.img. (highres should probably have been brain-extracted already using BET, and standard should probably be ${FSLDIR}/data/standard/MNI152_T1_2mm_brain)
- Carry out the above flirt and convert_xfm commands exactly as written.
- This should leave you with correctly named transform files which FEAT will automatically use when carrying out group statistics.

#### Stephen Smith and Mark Jenkinson
Copyright © 2000-2001, University of Oxford