PRELUDE DOCS

# PRELUDE - Phase Unwrapping Phase Region Expanding Labeller for Unwrapping Discrete Estimates |

## PRELUDE

prelude performs 3D phase unwrapping of images. This is useful for fieldmap acquisitions, susceptibility weighted imaging (SWI), or other applications involving phase in MR (or non-MR) images. The input can either be a single complex image (NIfTI or Analyze), or a pair of real images giving the phase and absolute values separately. Also see fslcomplex for more ways to manipulate complex image formats.

If the images are 4D images, then each 3D volume is unwrapped separately, and the result saved as a 4D image of unwrapped phase images. The output in either case is a real, unwrapped phase image (in radians).

For higher resolution images (e.g. for Susceptibility Weighted Imaging) a mask should be used in order to reduce run-times since any areas that include noisy voxels will significantly increase the required run-time. The best way to generate a mask for a whole brain image is to run BET to perform brain extraction on the absolute image.

The three main forms of usage are:

prelude -c data -u result
  uses a single complex input file
prelude -a data_abs -p data_phase -u result
  uses separate phase and absolute input files
prelude -a data_abs -p data_phase -u result -m mask
  uses separate phase and absolute input files with a mask

Additional options that are useful are:

-m mask
  uses the user-defined mask (e.g. a BET mask - especially for high resolution images)
-n num
  specifies the number of phase partitions the algorithm uses for initial labelling - a larger value is likely to be more robust but slower
-s
  unwrap in 2D, then stick slices together with appropriate offsets - this is less robust but fast - mainly used for very high-resolution images where optimising speed is an issue
--labelslices
  does labelling in 2D, but unwrapping in 3D - the default for high-res images

#### Mark Jenkinson
Copyright © 2001-2010, University of Oxford