> I have been looking around for a script to do all the preprocessing
> (realignment, corregistration, Time slicing, normalization smoothing and
> segmentation). I already run the script for model specification and
> estimation that Karl distributed... but for the pre-processing, I could
> not find anything... even though in the SPM2 pages it says it works very
> nicely...
>
> could anyone give a tip on where could I find this????
Very soon, we hope to have a beta version of a batching toolbox for SPM
that should not involve needing too much Matlab programming. At the
moment, you can use command line versions of spm_realign, spm_segment,
spm_normalise, etc. Typing help, followed by the name of the function
will give you some help about how to use the functions. Alternatively,
the help system will give you the same information, in a way that may
be easier.
FORMAT P = spm_realign(P,flags)
P - matrix of filenames {one string per row}
All operations are performed relative to the first image.
ie. Coregistration is to the first image, and resampling
of images is into the space of the first image.
For multiple sessions, P should be a cell array, where each
cell should be a matrix of filenames.
flags - a structure containing various options. The fields are:
quality - Quality versus speed trade-off. Highest quality
(1) gives most precise results, whereas lower
qualities gives faster realignment.
The idea is that some voxels contribute little to
the estimation of the realignment parameters.
This parameter is involved in selecting the number
of voxels that are used.
fwhm - The FWHM of the Gaussian smoothing kernel (mm)
applied to the images before estimating the
realignment parameters.
sep - the default separation (mm) to sample the images.
rtm - Register to mean. If field exists then a two pass
procedure is to be used in order to register the
images to the mean of the images after the first
realignment.
PW - a filename of a weighting image (reciprocal of
standard deviation). If field does not exist, then
no weighting is done.
interp - B-spline degree used for interpolation
FORMAT params = spm_normalise(VG,VF,matname,VWG,VWF,flags)
VG - template handle(s)
VF - handle of image to estimate params from
matname - name of file to store deformation definitions
VWG - template weighting image
VWF - source weighting image
flags - flags. If any field is not passed, then defaults are assumed.
smosrc - smoothing of source image (FWHM of Gaussian in mm).
Defaults to 8.
smoref - smoothing of template image (defaults to 0).
regtype - regularisation type for affine registration
See spm_affreg.m (default = 'mni').
cutoff - Cutoff of the DCT bases. Lower values mean more
basis functions are used (default = 30mm).
nits - number of nonlinear iterations (default=16).
reg - amount of regularisation (default=0.1)
FORMAT VO = spm_segment(PF,PG,flags)
PF - name(s) of image(s) to segment (must have same dimensions).
PG - name(s) of template image(s) for realignment.
- or a 4x4 transformation matrix which maps from the image to
the set of templates.
flags - a structure normally based on defaults.segment
VO - optional output volume
FORMAT spm_reslice(P,flags)
P - matrix of filenames {one string per row}
All operations are performed relative to the first image.
ie. Coregistration is to the first image, and resampling
of images is into the space of the first image.
flags - a structure containing various options. The fields are:
mask - mask output images (1 for yes, 0 for no)
To avoid artifactual movement-related variance the realigned
set of images can be internally masked, within the set (i.e.
if any image has a zero value at a voxel than all images have
zero values at that voxel). Zero values occur when regions
'outside' the image are moved 'inside' the image during
realignment.
mean - write mean image (1 for yes, 0 for no)
The average of all the realigned scans is written to
mean*.img.
interp - the B-spline interpolation method.
Non-finite values result in Fourier interpolation. Note that
Fourier interpolation only works for purely rigid body
transformations. Voxel sizes must all be identical and
isotropic.
which - Values of 0, 1 or 2 are allowed.
0 - don't create any resliced images.
Useful if you only want a mean resliced image.
1 - don't reslice the first image.
The first image is not actually moved, so it may not be
necessary to resample it.
2 - reslice all the images.
The spatially realigned images are written to the orginal
subdirectory with the same filename but prefixed with an 'r'.
They are all aligned with the first.
FORMAT VO = spm_write_sn(V,prm,flags,msk)
V - Images to transform (filenames or volume structure).
matname - Transformation information (filename or structure).
flags - flags structure, with fields...
interp - interpolation method (0-7)
wrap - wrap edges (e.g., [1 1 0] for 2D MRI sequences)
vox - voxel sizes (3 element vector - in mm)
Non-finite values mean use template vox.
bb - bounding box (2x3 matrix - in mm)
Non-finite values mean use template bb.
preserve - either 0 or 1. A value of 1 will "modulate"
the spatially normalised images so that total
units are preserved, rather than just
concentrations.
msk - An optional cell array for masking the spatially
normalised images.
Best regards,
-John
--
Dr John Ashburner.
Functional Imaging Lab., 12 Queen Square, London WC1N 3BG, UK.
tel: +44 (0)20 78337491 or +44 (0)20 78373611 x4381
fax: +44 (0)20 78131420 http://www.fil.ion.ucl.ac.uk/~john
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