minctracc - a program to automatically find the best linear
transformation to map one volumetric data set on to another. The
program uses optimization over a user selctable number of
parameters
to identify the best (according to a user identified objective
function) transformation mapping voxel values of the first data
set
into the second.
GENERAL DESCRIPTION; INPUTS AND OUTPUTS
You need to specify at least two data volumes on the command line, the
first is the source volume and second is the target volume. The third
item on the command line is the name of the output transformation
file, specifying where the program will store the results.
Using flags on the command line, you may specify the type of
transformation to be optimized and saved, mask files to be used with
the source or target volumes, a transformation file to specify the
initial starting condition, the type of objective function to be
minimized, the type of interpolation to use, and the definition of the
sampling matrix used to measure the objective function.
Internally, the program optimizes the transformation parameters of
translations, rotations, scaling(s) and possibly shear(s). These
parameters are used to create a homogeneous transformation matrix that
maps the data in the space of the first volume to the space of the
second volume. It is this matrix that is saved in the output
transformation file.
SLIGHTLY MORE DETAILED DESCRIPTIONS:
----- Initial Starting Position ----There are two basic methods to get an initial transformation to start
the optimization process. The first, by default, uses the principal
axes transformation (PAT) as the starting transformation. For the
second method, the user specifies a .xfm file that contains a linear
transformation, mapping points of volume one (source) into volume two
(target).
The program extracts the transformation parameters from either
transformation matrix (PAT or user input) and optimizes these
parameters when trying to find the best transformation.
When the PAT is used, the center of rotation and scaling is
automatically estimated from the center of gravity of the source data
set. When the user specifies a transformation matrix, the default
center is 0,0,0. The user can can change this in two ways: 1) the
-center cx cy cz option permits direct input of the center to be used,
2) the -est_center option tells the program to calculate and use the
center of gravity of the source volume. Note that it is a good idea
to have a reasonable guess for the center of rotation and scaling
since it makes the parameters more orthogonal to each other (e.g. a
small change in rotation will not grossly affect the translations).
Note that you can use -est_center to have the program estimate the
center of gravity.
From minctracc -help:
Initial transformation information.
-transformation:
Initial world transformation. (Default = identity).
-est_center:
use center estimated from Principal axis trans.
-est_scales:
use scales estimated from Principal axis trans.
-est_rotations:
use rotations estimated from Principal axis trans.
-est_translations: use translations estimated from Principal axis
trans.
-center:
Force center of rotation and scale.
Default value: 0 0 0
One can also use only part of the PAT parameters by specifying
-est_center, -est_scales, -est_rotations or -est_translations. Often
we have found that when the principal axis are difficult to determine
(as in cases of data sets with few slices) that the center and
translation are the only reliable information that can be determined.
So the parameters '-est_center -est_translations' are used to specify
the initial starting position.
----- Type of transformation to be optimized ----There are a number of different transformations that can be optimized.
Each one is specified by a flag on the command line. This information
is used internally to control the number of the parameters that are
modified by the optimization algorithm. (Only the resulting
transformation matrix is returned in the output .xfm file.) The
default is the -procrustes transformation.
The choices are:
-pat
return the matrix determined by the principal axes
transformation.
-lsq6
return the six parameter registration matrix. the six
parameters are translation x,y,z and rotation x,y,z.
-lsq7
return the seven parameter registration matrix. the
parameters are translation x,y,z and rotation x,y,z and
one global scale.
-lsq9
return the seven parameter registration matrix. the
parameters are translation x,y,z and rotation x,y,z and
scale x,y,z.
-lsq12
return full 12 parameter transformation. the
parameters
are translation x,y,z; rotation x,y,z; scale x,y,z and
shear x,y,z.
-procrustes
same as -lsq7
The user can also specify whether the forward (from source to model)
or inverse (from model to source) transformation should be recovered.
These flags are:
-forward:
default).
-invert:
Recover forward transformation (source -> model,
Recover inverted transformation (model -> source).
----- Sampling information ------The objective function will be evaluated at points defined on a 3D
lattice that covers the volumes that have to be fit. The spacing
between these lattice points must be specified.
-step
is the option that specifies the distance between points
in the 3D lattice. Normally, one should set -step to be
equal to less than half the fwhm of the blurring kernel of
the data to be fit.
----- Type of objective function to be minimized ----There are four different objective functions that can be used for
minimization in the optimization routines. These functions are
cross-correlation, normalized intensity difference, stochastic sign
change and minimization of the variance of the pixel ratios
(vol1/vol2). When masks are specified on the command line, only data
in the masked region participates in the evaluation of the objective
function.
from minctracc -help:
Optimization objective functions. (default = -xcorr)
-xcorr:
Use cross correlation.
-zscore:
Use normalized difference.
-ssc:
Use stocastic sign change.
-vr:
Use variance of ratio vol1/vol2
-groups:
Number of groups for ratio calculations.
Default value: 16
-threshold:
Lower limit for voxel threshold
Default value: 0 0
-speckle:
percent speckle noise to add to source
Default value: 5
-xcorr: cross correlation: the value returned has a maximum value of 1
and
a minimum value of 0. The correlation value is calculated as:
r =
f1 / ( sqrt(f2) * sqrt(f3) )
where:
f1 = sum( d1 .* d2)
f2 = sum( d1 .^ 2 )
f3 = sum( d2 .^ 2 )
(point to point multiply)
(sum of all points squared)
(sum of all points squared)
-zscore: normalized intensity. For both source and target volumes,
each pixel in the volume is replaced by
v' = (v-u)/std
where
v is the old voxel value,
u is the mean voxel value (within the mask) for the one volume
std is the standard deviation of voxels (in the mask) for the
volume.
the objective function is:
__
z = 1/ \
/n /_
| v'1 - v'2 | ; where the summation is done
over all voxels.
-ssc: stochastic sign change - see Minoshima
-speckle option is used to specify the percent speckle noise
to add to the source volume
-vr:
variance of ratio
- see Woods
-groups is used to specify the number of classification
groups to be used when calculating the variance.
-threshold specifies the two threshold values form vol1 and vol2
----- Optimization info -----Simplex optimization is used to find the best transformation by
varying the parameters. There are two user inputs to control the
optimization:
-tolerance - stopping criteria for fitting. The routine will end when
the (max(f_simplex) - min(f_simplex))
--------------------------------- < tol
(max(f_simplex) + min(f_simplex))
where f_simplex is the value of the objective function
evaluated at each vertex on the simplex.
-simplex
- starting size (diameter) for simplex. This is measured
in mm for spatial axes, degrees for rotation axes and
percentage scale for scaling axes.
----- Other Stuff -------
Options for mask volumes.
The voxel masks do not have to be voxel-to-voxel matched with the
data. The world coordinate system is used to determine if a point
from is within the masked area or not.
-model_mask:
Specifies a binary mask file for the target.
Voxels of the target model that map to zero valued
voxels in the mask are masked OUT of the data (these
points will NOT participate in the fit).
-source_mask: Specifies a binary mask file for the source.
Interpolation options.
-trilinear:
Do trilinear interpolation
-tricubic:
Do tricubic interpolation
-nearest_neighbour: Do nearest neighbour interpolation
other flags:
-verbose - levels of verbose messages, default = 1
0=quiet, or maybe:
1=show optimization info
2=show objective function info
3=show fitting summary (of optimization and objetive fn)
-debug - show debugging information during the run.
----------------------------------------------------------------------OUTPUT of minctracc -help
Command-specific options:
---Transformation maps one to volume two--Initial transformation information.
-no_clobber:
Do not overwrite output file (default).
-clobber:
Overwrite output file.
-transformation:
Initial world transformation. (Default = identity).
-est_center:
use center estimated from Principal axis trans.
-est_scales:
use scales estimated from Principal axis trans.
-est_rotations:
use rotations estimated from Principal axis trans.
-est_translations: use translations estimated from Principal axis
trans.
-center:
Force center of rotation and scale.
Default value: 0 0 0
Output transformation type. Default = -procrustes.
-pat:
principal axis transformation matrix (input matrix
ignored).
-lsq6:
6 parameter transformation (3 translation, 3
rotation, scale=1.0).
-lsq7:
7 parameter transformation (lsq6 + 1 global scale,
same as -procrustes).
-lsq9:
9 parameter transformation (lsq6 + 3 scales).
-lsq12:
full 12 parameter transformation (lsq9 + 3 shears).
-lsq:
full 12 parameter transformation (same as -lsq12).
-procrustes:
procrustes transformation (3 trans, 3 rots, 1
scale), same as -lsq7.
-forward:
Recover forward transformation (source -> model,
default).
-invert:
Recover inverted transformation (model -> source).
Options for mask volumes.
-model_mask:
Specifies a binary mask file for the target.
-source_mask:
Specifies a binary mask file for the source.
Interpolation options.
-trilinear:
Do trilinear interpolation
-tricubic:
Do tricubic interpolation
-nearest_neighbour: Do nearest neighbour interpolation
Optimization objective functions. (default = -xcorr)
-xcorr:
Use cross correlation.
-zscore:
Use normalized difference.
-ssc:
Use stocastic sign change.
-vr:
Use variance of ratio vol1/vol2
-groups:
Number of groups for ratio calculations.
Default value: 16
-threshold:
Lower limit for voxel threshold
Default value: 0 0
-speckle:
percent speckle noise to add to source
Default value: 5
Options for optimization.
-tol:
Stopping criteria tolerence
Default value: 0.005
-simplex:
Radius of simplex volume.
Default value: 20
Options for measurement comparison.
-matlab:
Output selected objective function value curves.
-measure:
Output value of each obj. func. for given x-form.
Options for 3D lattice (default = target).
-step:
Step size along each dimension (X, Y, Z)
Default value: 4 4 4
-xstep:
Step size along the column dimension
Default value: 4
-ystep:
Step size along the row dimension
Default value: 4
-zstep:
Step size along the slice dimension
Default value: 4
Options for logging progress. Default = -verbose 1.
-verbose:
Write messages indicating progress
Default value: 1
-quiet:
Do not write log messages
-debug:
Print out debug info.
Generic options for all commands:
-help:
Print summary of command-line options and abort
Usage: minctracc [<options>] <sourcefile> <targetfile> <output transfile>
minctracc [-help]