FT_VOLUMENORMALISE
Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_volumenormalise”.
FT_VOLUMENORMALISE normalises anatomical and functional volume data to a template anatomical MRI. Use as [mri] = ft_volumenormalise(cfg, mri) where the input mri should be a single anatomical volume that was for example read with FT_READ_MRI. Configuration options are cfg.spmversion = string, 'spm2', 'spm8', 'spm12' (default = 'spm8') cfg.template = string, filename of the template anatomical MRI (default = 'T1.mnc' for spm2 or 'T1.nii' for spm8) cfg.parameter = cell-array with the functional data to be normalised (default = 'all') cfg.downsample = integer number (default = 1, i.e. no downsampling) cfg.name = string for output filename cfg.write = 'no' (default) or 'yes', writes the segmented volumes to SPM2 compatible analyze-file, with the suffix _anatomy for the anatomical MRI volume _param for each of the functional volumes cfg.nonlinear = 'yes' (default) or 'no', estimates a nonlinear transformation in addition to the linear affine registration. If a reasonably accurate normalisation is sufficient, a purely linearly transformed image allows for 'reverse-normalisation', which might come in handy when for example a region of interest is defined on the normalised group-average. To facilitate data-handling and distributed computing you can use cfg.inputfile = ... cfg.outputfile = ... If you specify one of these (or both) the input data will be read from a *.mat file on disk and/or the output data will be written to a *.mat file. These mat files should contain only a single variable, corresponding with the input/output structure. See also FT_READ_MRI, FT_VOLUMEDOWNSAMPLE, FT_SOURCEINTERPOLATE, FT_SOURCEPLOT