# mritotal.default.cfg
#
# This is the default protocol file for mritotal, which specifies all
# the data-specific preprocessing steps to take.  Note that you don't
# have any control over the order of the preprocessing steps -- you
# can only specify what is done, and how it is done.  The order of
# steps taken is as follows:
#
#    * reduce data (subsample and crop)
#    * zero-pad data (necessary to ensure that blurring is correct)
#    * blur data
#

# Default protocol by Greg Ward 95/08/23 - this instructs mritotal to
# use some simple heuristics to subsample and crop the data, and
# should work with T1-weighted MRI data of *normal* human brains where
# the top of the head is pretty close to the top of the scanning
# volume.  You can also explicitly set the subsampling and cropping
# parameters if you know that your scanning protocol is quite
# consistent and would prefer not to have mritotal take a guess every
# time it runs; see mritotal.icbm.cfg for an example of how this is
# done for the ICBM protocol.



# The data is first subsampled, mainly to save memory and time.  There
# are four possible actions here:
#   * -nosubsample: mritotal will not subsample your data
#   * -subsample xstep ystep zstep: you specify separate step sizes
#     (sampling frequencies) for each of the three spatial dimensions
#   * -isosubsample step: you specify a single step for all three 
#     dimensions
#   * -guess_subsample: mritotal will compute the step sizes based
#     on your data.  The step sizes for the three dimensions
#     are calculated independently; if your input step is < 1.5mm, 
#     then the subsampling step will be twice your input step;
#     otherwise, that dimension is not subsampled.

-guess_subsample

# At the same time that the data is subsampled, it is cropped.  This
# is more important than subsampling, as the fit may fail if there is
# too much data (eg. if the scanning volume extends down into the
# neck, as is often the case with coronal or sagittal acquisitions).
# You have the same four options for cropping as for subsampling
# (-nocrop, -crop, -isocrop, and -guess_crop), except that "-crop" and
# "-isocrop" take rather more complicated arguments.
#
# In particular, they expect pairs of numbers (-crop expects three,
# -isocrop only one) that specify the amount to chop off each end of
# an axis.  (Actually, these numbers specify how much to *extend* the
# axis by, so you must give negative numbers to chop data off.)  The
# first number specifies how much to chop off the low end of the axis,
# and the second specifies how much to chop off the high end.  Note
# that these are "low" and "high" in the sense implied by the MINC
# standard, ie. the low end of the x axis is the patient's left, low y
# is patient posterior, and low z is patient inferior -- independent
# of the order or orientation of your data.  Finally, the numbers can
# be specified in voxels, millimetres, or as a percentage of the
# original dimension extent.
#
# In this default protocol, we use mritotal's simple heuristic for
# cropping, which is: leave the x and y dimensions alone, but chop off
# anything more than 190mm below the top of the volume.  As long as
# the top of the subject's head is pretty close to the top of the
# volume, this does a reasonable job of chopping out excess data
# (ie. below the bottom of the cerebellum).
# 
# As a slightly fancier example, the crop specification for the ICBM
# protocol is "-crop 0,0 0,0 -25%,0". This illustrates how to chop off
# 25% of the data at the bottom of the scan (low z) while leaving the
# x and y axes alone.  (Since ICBM scans have a z extent of 256 mm,
# this has the effect of removing all but the top 192mm of the scan,
# which is almost identical to mritotal's cropping heuristic.)  You
# can also specify crop amounts as mm (millimetres) or v (voxels);
# eg. to remove 10 voxels at both ends of the x axis and 20mm at the
# top of the head (high z), you would use "-crop -10v,-10v 0,0
# 0,-20mm".  You can mix and match the three units at will; for
# instance, you could chop 25% at the bottom, and 10 voxels at the
# top, of the z axis with "-crop 0,0 0,0 -25%,-10v".  If no unit is
# specified, mm is assumed.

-guess_crop

# Specify the objective function used for fitting.  You can use
# any of the objective functions supported by minctracc (do 
# "minctracc -help" for an up-to-date list); currently, these
# are:
# 
#    xcorr   cross-correlation
#    mi      mutual information [Collignon]
#    vr      variance of ratios [Woods]
#    zscore  normalized difference
#    ssc     stochasic sign change
#
# Only xcorr has been thoroughly tested and routinely used for
# fitting MRI data to Talairach space.

-objective xcorr