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**PROGRAM:**

**NAME**

mia-3drigidreg - Linear registration of 3D images.

**SYNOPSIS**

**mia-3drigidreg**

**-i**

**<in-image>**

**-r**

**<ref-image>**

**-o**

**<out-image>**

**[options]**

**DESCRIPTION**

**mia-3drigidreg**This program implements the registration of two gray scale 3D images. The

transformation is not penalized, therefore, one should only use translation, rigid, or

affine transformations as target and run mia-3dnonrigidreg of nonrigid registration is to

be achieved.

**OPTIONS**

**File**

**I/O**

-i --in-image=(input, required); io

test image For supported file types see PLUGINS:3dimage/io

-r --ref-image=(input, required); io

reference image For supported file types see PLUGINS:3dimage/io

-o --out-image=(output, required); io

registered output image For supported file types see PLUGINS:3dimage/io

-t --transformation=(output); io

transformation output file name For supported file types see

PLUGINS:3dtransform/io

-c --cost=ssd

cost functioncost function For supported plugins see PLUGINS:3dimage/cost

-l --levels=3

multigrid levelsmultigrid levels

-O --optimizer=gsl:opt=simplex,step=1.0

Optimizer used for minimizationOptimizer used for minimization For

supported plugins see PLUGINS:minimizer/singlecost

-f --transForm=rigid

transformation typetransformation type For supported plugins see

PLUGINS:3dimage/transform

**Help**

**&**

**Info**

-V --verbose=warning

verbosity of output, print messages of given level and higher priorities.

Supported priorities starting at lowest level are:

__info__‐ Low level messages

__trace__‐ Function call trace

__fail__‐ Report test failures

__warning__‐ Warnings

__error__‐ Report errors

__debug__‐ Debug output

__message__‐ Normal messages

__fatal__‐ Report only fatal errors

--copyright

print copyright information

-h --help

print this help

-? --usage

print a short help

--version

print the version number and exit

**Processing**

--threads=-1

Maxiumum number of threads to use for processing,This number should be lower

or equal to the number of logical processor cores in the machine. (-1:

automatic estimation).Maxiumum number of threads to use for processing,This

number should be lower or equal to the number of logical processor cores in

the machine. (-1: automatic estimation).

**PLUGINS:** **1d/splinebc**

**mirror**Spline interpolation boundary conditions that mirror on the boundary

(no parameters)

**repeat**Spline interpolation boundary conditions that repeats the value at the boundary

(no parameters)

**zero**Spline interpolation boundary conditions that assumes zero for values outside

(no parameters)

**PLUGINS:** **1d/splinekernel**

**bspline**B-spline kernel creation , supported parameters are:

__d__= 3; int in [0, 5]

Spline degree.

**omoms**OMoms-spline kernel creation, supported parameters are:

__d__= 3; int in [3, 3]

Spline degree.

**PLUGINS:** **3dimage/cost**

**lncc**local normalized cross correlation with masking support., supported parameters

are:

__w__= 5; uint in [1, 256]

half width of the window used for evaluating the localized cross

correlation.

**mi**Spline parzen based mutual information., supported parameters are:

__cut__= 0; float in [0, 40]

Percentage of pixels to cut at high and low intensities to remove

outliers.

__mbins__= 64; uint in [1, 256]

Number of histogram bins used for the moving image.

__mkernel__= [bspline:d=3]; factory

Spline kernel for moving image parzen hinstogram. For supported plug-ins

see PLUGINS:1d/splinekernel

__rbins__= 64; uint in [1, 256]

Number of histogram bins used for the reference image.

__rkernel__= [bspline:d=0]; factory

Spline kernel for reference image parzen hinstogram. For supported plug-

ins see PLUGINS:1d/splinekernel

**ncc**normalized cross correlation.

(no parameters)

**ngf**This function evaluates the image similarity based on normalized gradient

fields. Given normalized gradient fields $ _S$ of the src image and $ _R$ of the

ref image various evaluators are implemented., supported parameters are:

__eval__= ds; dict

plugin subtype (sq, ds,dot,cross). Supported values are:

__ds__‐ square of scaled difference

__dot__‐ scalar product kernel

__cross__‐ cross product kernel

**ssd**3D image cost: sum of squared differences, supported parameters are:

__autothresh__= 0; float in [0, 1000]

Use automatic masking of the moving image by only takeing intensity values

into accound that are larger than the given threshold.

__norm__= 0; bool

Set whether the metric should be normalized by the number of image pixels.

**ssd-automask**

3D image cost: sum of squared differences, with automasking based on given

thresholds, supported parameters are:

__rthresh__= 0; double

Threshold intensity value for reference image.

__sthresh__= 0; double

Threshold intensity value for source image.

**PLUGINS:** **3dimage/io**

**analyze**Analyze 7.5 image

Recognized file extensions: .HDR, .hdr

Supported element types:

unsigned 8 bit, signed 16 bit, signed 32 bit, floating point 32 bit,

floating point 64 bit

**datapool**Virtual IO to and from the internal data pool

Recognized file extensions: .@

**dicom**Dicom image series as 3D

Recognized file extensions: .DCM, .dcm

Supported element types:

signed 16 bit, unsigned 16 bit

**hdf5**HDF5 3D image IO

Recognized file extensions: .H5, .h5

Supported element types:

binary data, signed 8 bit, unsigned 8 bit, signed 16 bit, unsigned 16 bit,

signed 32 bit, unsigned 32 bit, signed 64 bit, unsigned 64 bit, floating

point 32 bit, floating point 64 bit

**inria**INRIA image

Recognized file extensions: .INR, .inr

Supported element types:

signed 8 bit, unsigned 8 bit, signed 16 bit, unsigned 16 bit, signed 32

bit, unsigned 32 bit, floating point 32 bit, floating point 64 bit

**mhd**MetaIO 3D image IO using the VTK implementation (experimental).

Recognized file extensions: .MHA, .MHD, .mha, .mhd

Supported element types:

signed 8 bit, unsigned 8 bit, signed 16 bit, unsigned 16 bit, signed 32

bit, unsigned 32 bit, floating point 32 bit, floating point 64 bit

**nifti**NIFTI-1 3D image IO

Recognized file extensions: .NII, .nii

Supported element types:

signed 8 bit, unsigned 8 bit, signed 16 bit, unsigned 16 bit, signed 32

bit, unsigned 32 bit, signed 64 bit, unsigned 64 bit, floating point 32

bit, floating point 64 bit

**vff**VFF Sun raster format

Recognized file extensions: .VFF, .vff

Supported element types:

unsigned 8 bit, signed 16 bit

**vista**Vista 3D

Recognized file extensions: .V, .VISTA, .v, .vista

Supported element types:

binary data, signed 8 bit, unsigned 8 bit, signed 16 bit, unsigned 16 bit,

signed 32 bit, unsigned 32 bit, floating point 32 bit, floating point 64

bit

**vti**3D image VTK-XML in- and output (experimental).

Recognized file extensions: .VTI, .vti

Supported element types:

signed 8 bit, unsigned 8 bit, signed 16 bit, unsigned 16 bit, signed 32

bit, unsigned 32 bit, floating point 32 bit, floating point 64 bit

**vtk**3D VTK image legacy in- and output (experimental).

Recognized file extensions: .VTK, .VTKIMAGE, .vtk, .vtkimage

Supported element types:

binary data, signed 8 bit, unsigned 8 bit, signed 16 bit, unsigned 16 bit,

signed 32 bit, unsigned 32 bit, floating point 32 bit, floating point 64

bit

**PLUGINS:** **3dimage/transform**

**affine**Affine transformation (12 degrees of freedom), supported parameters are:

__imgboundary__= mirror; factory

image interpolation boundary conditions. For supported plug-ins see

PLUGINS:1d/splinebc

__imgkernel__= [bspline:d=3]; factory

image interpolator kernel. For supported plug-ins see

PLUGINS:1d/splinekernel

**axisrot**Restricted rotation transformation (1 degrees of freedom). The transformation is

restricted to the rotation around the given axis about the given rotation

center, supported parameters are:

__axis__=(required, 3dfvector)

rotation axis.

__imgboundary__= mirror; factory

image interpolation boundary conditions. For supported plug-ins see

PLUGINS:1d/splinebc

__imgkernel__= [bspline:d=3]; factory

image interpolator kernel. For supported plug-ins see

PLUGINS:1d/splinekernel

__origin__=(required, 3dfvector)

center of the transformation.

**raffine**Restricted affine transformation (3 degrees of freedom). The transformation is

restricted to the rotation around the given axis and shearing along the two axis

perpendicular to the given one, supported parameters are:

__axis__=(required, 3dfvector)

rotation axis.

__imgboundary__= mirror; factory

image interpolation boundary conditions. For supported plug-ins see

PLUGINS:1d/splinebc

__imgkernel__= [bspline:d=3]; factory

image interpolator kernel. For supported plug-ins see

PLUGINS:1d/splinekernel

__origin__=(required, 3dfvector)

center of the transformation.

**rigid**Rigid transformation, i.e. rotation and translation (six degrees of freedom).,

supported parameters are:

__imgboundary__= mirror; factory

image interpolation boundary conditions. For supported plug-ins see

PLUGINS:1d/splinebc

__imgkernel__= [bspline:d=3]; factory

image interpolator kernel. For supported plug-ins see

PLUGINS:1d/splinekernel

__origin__= [[0,0,0]]; 3dfvector

Relative rotation center, i.e. <0.5,0.5,0.5> corresponds to the center of

the volume.

**rotation**Rotation transformation (three degrees of freedom)., supported parameters are:

__imgboundary__= mirror; factory

image interpolation boundary conditions. For supported plug-ins see

PLUGINS:1d/splinebc

__imgkernel__= [bspline:d=3]; factory

image interpolator kernel. For supported plug-ins see

PLUGINS:1d/splinekernel

__origin__= [[0,0,0]]; 3dfvector

Relative rotation center, i.e. <0.5,0.5,0.5> corresponds to the center of

the volume.

**rotbend**Restricted transformation (4 degrees of freedom). The transformation is

restricted to the rotation around the x and y axis and a bending along the x

axis, independedn in each direction, with the bending increasing with the

squared distance from the rotation axis., supported parameters are:

__imgboundary__= mirror; factory

image interpolation boundary conditions. For supported plug-ins see

PLUGINS:1d/splinebc

__imgkernel__= [bspline:d=3]; factory

image interpolator kernel. For supported plug-ins see

PLUGINS:1d/splinekernel

__norot__= 0; bool

Don't optimize the rotation.

__origin__=(required, 3dfvector)

center of the transformation.

**spline**Free-form transformation that can be described by a set of B-spline coefficients

and an underlying B-spline kernel., supported parameters are:

__anisorate__= [[0,0,0]]; 3dfvector

anisotropic coefficient rate in pixels, nonpositive values will be

overwritten by the 'rate' value..

__debug__= 0; bool

enable additional debuging output.

__imgboundary__= mirror; factory

image interpolation boundary conditions. For supported plug-ins see

PLUGINS:1d/splinebc

__imgkernel__= [bspline:d=3]; factory

image interpolator kernel. For supported plug-ins see

PLUGINS:1d/splinekernel

__kernel__= [bspline:d=3]; factory

transformation spline kernel. For supported plug-ins see

PLUGINS:1d/splinekernel

__penalty__= ; factory

transformation penalty energy term. For supported plug-ins see

PLUGINS:3dtransform/splinepenalty

__rate__= 10; float in [1, inf)

isotropic coefficient rate in pixels.

**translate**Translation (three degrees of freedom), supported parameters are:

__imgboundary__= mirror; factory

image interpolation boundary conditions. For supported plug-ins see

PLUGINS:1d/splinebc

__imgkernel__= [bspline:d=3]; factory

image interpolator kernel. For supported plug-ins see

PLUGINS:1d/splinekernel

**vf**This plug-in implements a transformation that defines a translation for each

point of the grid defining the domain of the transformation., supported

parameters are:

__imgboundary__= mirror; factory

image interpolation boundary conditions. For supported plug-ins see

PLUGINS:1d/splinebc

__imgkernel__= [bspline:d=3]; factory

image interpolator kernel. For supported plug-ins see

PLUGINS:1d/splinekernel

**PLUGINS:** **3dtransform/io**

**bbs**Binary (non-portable) serialized IO of 3D transformations

Recognized file extensions: .bbs

**datapool**Virtual IO to and from the internal data pool

Recognized file extensions: .@

**vista**Vista storage of 3D transformations

Recognized file extensions: .v, .v3dt

**xml**XML serialized IO of 3D transformations

Recognized file extensions: .x3dt

**PLUGINS:** **3dtransform/splinepenalty**

**divcurl**divcurl penalty on the transformation, supported parameters are:

__curl__= 1; float in [0, inf)

penalty weight on curl.

__div__= 1; float in [0, inf)

penalty weight on divergence.

__norm__= 0; bool

Set to 1 if the penalty should be normalized with respect to the image

size.

__weight__= 1; float in (0, inf)

weight of penalty energy.

**PLUGINS:** **minimizer/singlecost**

**gdas**Gradient descent with automatic step size correction., supported parameters are:

__ftolr__= 0; double in [0, inf)

Stop if the relative change of the criterion is below..

__max-step__= 2; double in (0, inf)

Maximal absolute step size.

__maxiter__= 200; uint in [1, inf)

Stopping criterion: the maximum number of iterations.

__min-step__= 0.1; double in (0, inf)

Minimal absolute step size.

__xtola__= 0.01; double in [0, inf)

Stop if the inf-norm of the change applied to x is below this value..

**gdsq**Gradient descent with quadratic step estimation, supported parameters are:

__ftolr__= 0; double in [0, inf)

Stop if the relative change of the criterion is below..

__gtola__= 0; double in [0, inf)

Stop if the inf-norm of the gradient is below this value..

__maxiter__= 100; uint in [1, inf)

Stopping criterion: the maximum number of iterations.

__scale__= 2; double in (1, inf)

Fallback fixed step size scaling.

__step__= 0.1; double in (0, inf)

Initial step size.

__xtola__= 0; double in [0, inf)

Stop if the inf-norm of x-update is below this value..

**gsl**optimizer plugin based on the multimin optimizers ofthe GNU Scientific Library

(GSL) https://www.gnu.org/software/gsl/, supported parameters are:

__eps__= 0.01; double in (0, inf)

gradient based optimizers: stop when |grad| < eps, simplex: stop when

simplex size < eps..

__iter__= 100; uint in [1, inf)

maximum number of iterations.

__opt__= gd; dict

Specific optimizer to be used.. Supported values are:

__bfgs__‐ Broyden-Fletcher-Goldfarb-Shann

__bfgs2__‐ Broyden-Fletcher-Goldfarb-Shann (most efficient version)

__cg-fr__‐ Flecher-Reeves conjugate gradient algorithm

__gd__‐ Gradient descent.

__simplex__‐ Simplex algorithm of Nelder and Mead

__cg-pr__‐ Polak-Ribiere conjugate gradient algorithm

__step__= 0.001; double in (0, inf)

initial step size.

__tol__= 0.1; double in (0, inf)

some tolerance parameter.

**nlopt**Minimizer algorithms using the NLOPT library, for a description of the

optimizers please see 'http://ab-

initio.mit.edu/wiki/index.php/NLopt_Algorithms', supported parameters are:

__ftola__= 0; double in [0, inf)

Stopping criterion: the absolute change of the objective value is below

this value.

__ftolr__= 0; double in [0, inf)

Stopping criterion: the relative change of the objective value is below

this value.

__higher__= inf; double

Higher boundary (equal for all parameters).

__local-opt__= none; dict

local minimization algorithm that may be required for the main

minimization algorithm.. Supported values are:

__gn-orig-direct-l__‐ Dividing Rectangles (original implementation,

locally biased)

__gn-direct-l-noscal__‐ Dividing Rectangles (unscaled, locally biased)

__gn-isres__‐ Improved Stochastic Ranking Evolution Strategy

__ld-tnewton__‐ Truncated Newton

__gn-direct-l-rand__‐ Dividing Rectangles (locally biased, randomized)

__ln-newuoa__‐ Derivative-free Unconstrained Optimization by Iteratively

Constructed Quadratic Approximation

__gn-direct-l-rand-noscale__‐ Dividing Rectangles (unscaled, locally

biased, randomized)

__gn-orig-direct__‐ Dividing Rectangles (original implementation)

__ld-tnewton-precond__‐ Preconditioned Truncated Newton

__ld-tnewton-restart__‐ Truncated Newton with steepest-descent restarting

__gn-direct__‐ Dividing Rectangles

__ln-neldermead__‐ Nelder-Mead simplex algorithm

__ln-cobyla__‐ Constrained Optimization BY Linear Approximation

__gn-crs2-lm__‐ Controlled Random Search with Local Mutation

__ld-var2__‐ Shifted Limited-Memory Variable-Metric, Rank 2

__ld-var1__‐ Shifted Limited-Memory Variable-Metric, Rank 1

__ld-mma__‐ Method of Moving Asymptotes

__ld-lbfgs-nocedal__‐ None

__ld-lbfgs__‐ Low-storage BFGS

__gn-direct-l__‐ Dividing Rectangles (locally biased)

__none__‐ don't specify algorithm

__ln-bobyqa__‐ Derivative-free Bound-constrained Optimization

__ln-sbplx__‐ Subplex variant of Nelder-Mead

__ln-newuoa-bound__‐ Derivative-free Bound-constrained Optimization by

Iteratively Constructed Quadratic Approximation

__ln-praxis__‐ Gradient-free Local Optimization via the Principal-Axis

Method

__gn-direct-noscal__‐ Dividing Rectangles (unscaled)

__ld-tnewton-precond-restart__‐ Preconditioned Truncated Newton with

steepest-descent restarting

__lower__= -inf; double

Lower boundary (equal for all parameters).

__maxiter__= 100; int in [1, inf)

Stopping criterion: the maximum number of iterations.

__opt__= ld-lbfgs; dict

main minimization algorithm. Supported values are:

__gn-orig-direct-l__‐ Dividing Rectangles (original implementation,

locally biased)

__g-mlsl-lds__‐ Multi-Level Single-Linkage (low-discrepancy-sequence,

require local gradient based optimization and bounds)

__gn-direct-l-noscal__‐ Dividing Rectangles (unscaled, locally biased)

__gn-isres__‐ Improved Stochastic Ranking Evolution Strategy

__ld-tnewton__‐ Truncated Newton

__gn-direct-l-rand__‐ Dividing Rectangles (locally biased, randomized)

__ln-newuoa__‐ Derivative-free Unconstrained Optimization by Iteratively

Constructed Quadratic Approximation

__gn-direct-l-rand-noscale__‐ Dividing Rectangles (unscaled, locally

biased, randomized)

__gn-orig-direct__‐ Dividing Rectangles (original implementation)

__ld-tnewton-precond__‐ Preconditioned Truncated Newton

__ld-tnewton-restart__‐ Truncated Newton with steepest-descent restarting

__gn-direct__‐ Dividing Rectangles

__auglag-eq__‐ Augmented Lagrangian algorithm with equality constraints

only

__ln-neldermead__‐ Nelder-Mead simplex algorithm

__ln-cobyla__‐ Constrained Optimization BY Linear Approximation

__gn-crs2-lm__‐ Controlled Random Search with Local Mutation

__ld-var2__‐ Shifted Limited-Memory Variable-Metric, Rank 2

__ld-var1__‐ Shifted Limited-Memory Variable-Metric, Rank 1

__ld-mma__‐ Method of Moving Asymptotes

__ld-lbfgs-nocedal__‐ None

__g-mlsl__‐ Multi-Level Single-Linkage (require local optimization and

bounds)

__ld-lbfgs__‐ Low-storage BFGS

__gn-direct-l__‐ Dividing Rectangles (locally biased)

__ln-bobyqa__‐ Derivative-free Bound-constrained Optimization

__ln-sbplx__‐ Subplex variant of Nelder-Mead

__ln-newuoa-bound__‐ Derivative-free Bound-constrained Optimization by

Iteratively Constructed Quadratic Approximation

__auglag__‐ Augmented Lagrangian algorithm

__ln-praxis__‐ Gradient-free Local Optimization via the Principal-Axis

Method

__gn-direct-noscal__‐ Dividing Rectangles (unscaled)

__ld-tnewton-precond-restart__‐ Preconditioned Truncated Newton with

steepest-descent restarting

__ld-slsqp__‐ Sequential Least-Squares Quadratic Programming

__step__= 0; double in [0, inf)

Initial step size for gradient free methods.

__stop__= -inf; double

Stopping criterion: function value falls below this value.

__xtola__= 0; double in [0, inf)

Stopping criterion: the absolute change of all x-values is below this

value.

__xtolr__= 0; double in [0, inf)

Stopping criterion: the relative change of all x-values is below this

value.

**EXAMPLE**

Register image test.v to image ref.v affine and write the registered image to reg.v. Use

two multiresolution levels and ssd as cost function.

mia-3drigidreg -i test.v -r ref.v -o reg.v -l 2 -f affine -c ssd

**AUTHOR(s)**

Gert Wollny

**COPYRIGHT**

This software is Copyright (c) 1999‐2015 Leipzig, Germany and Madrid, Spain. It comes

with ABSOLUTELY NO WARRANTY and you may redistribute it under the terms of the GNU

GENERAL PUBLIC LICENSE Version 3 (or later). For more information run the program with the

option '--copyright'.

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