Provided by: mia-tools_2.0.13-1_amd64 
NAME
mia-3dprealign-nonrigid - Registration of a series of 3D images.
SYNOPSIS
mia-3dprealign-nonrigid -i <in-file> -o <out-file> [options]
DESCRIPTION
mia-3dprealign-nonrigid This program runs the non-rigid registration of an image series by
first registering an already aligned subset of the images to one reference, and then by
registering the remaining images by using synthetic references. The is a 3D version of G.
Wollny, M-J Ledesma-Cabryo, P.Kellman, and A.Santos, "Exploiting Quasiperiodicity in
Motion Correction of Free-Breathing," IEEE Transactions on Medical Imaging, 29(8), 2010.
OPTIONS
File-IO
-i --in-file=(required)
input images following the naming pattern nameXXXX.ext For supported file
types see PLUGINS:3dimage/io
-o --out-file=(required)
file name base for registered files given as C-format string For supported
file types see PLUGINS:3dimage/io
--save-references
Save synthetic references to files refXXXX.v
Preconditions & Preprocessing
-k --skip=0
Skip images at the begin of the series
--preskip=20
Skip images at the beginning+skip of the series when searching for high
contrats image
--postskip=2
Skip images at the end of the series when searching for high contrats image
--max-candidates=20
maximum number of candidates for global reference image
-S --cost-series=image:cost=[ngf:eval=ds]
Const function to use for the analysis of the series For supported plugins
see PLUGINS:3dimage/fullcost
--ref-idx=
save reference index number to this file
Registration
-O --optimizer=gsl:opt=gd,step=0.01
Optimizer used for minimization For supported plugins see
PLUGINS:minimizer/singlecost
-l --mr-levels=3
multi-resolution levels
-f --transForm=spline
transformation type For supported plugins see PLUGINS:3dimage/transform
-1 --cost-subset=image:cost=[ngf:eval=ds]
Cost function for registration during the subset registration For supported
plugins see PLUGINS:3dimage/fullcost
-2 --cost-final=image:cost=ssd
Cost function for registration during the final registration For supported
plugins see PLUGINS:3dimage/fullcost
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
warning ‐ Warnings
error ‐ Report errors
fail ‐ Report test failures
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).
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)
Spline degree. in [0, 5]
omoms OMoms-spline kernel creation, supported parameters are:
d = 3 (int)
Spline degree. in [3, 3]
PLUGINS: 3dimage/fullcost
divcurl divcurl penalty cost function, supported parameters are:
curl = 1 (float)
penalty weight on curl. in [0, 3.40282e+38]
div = 1 (float)
penalty weight on divergence. in [0, 3.40282e+38]
weight = 1 (float)
weight of cost function. in [-1e+10, 1e+10]
image Generalized image similarity cost function that also handles multi-resolution
processing. The actual similarity measure is given es extra parameter.,
supported parameters are:
cost = ssd (string)
Cost function kernel.
debug = 0 (bool)
Save intermediate resuts for debugging.
ref = ref.@ (io)
Reference image. For supported file types see PLUGINS:3dimage/io
src = src.@ (io)
Study image. For supported file types see PLUGINS:3dimage/io
weight = 1 (float)
weight of cost function. in [-1e+10, 1e+10]
taggedssd Evaluates the Sum of Squared Differences similarity measure by using three
tagged image pairs. The cost function value is evaluated based on all image
pairs, but the gradient is composed by composing its component based on the tag
direction., supported parameters are:
refx = (required, io)
Reference image X-tag. For supported file types see PLUGINS:3dimage/io
refy = (required, io)
Reference image Y-tag. For supported file types see PLUGINS:3dimage/io
refz = (required, io)
Reference image Z-tag. For supported file types see PLUGINS:3dimage/io
srcx = (required, io)
Study image X-tag. For supported file types see PLUGINS:3dimage/io
srcy = (required, io)
Study image Y-tag. For supported file types see PLUGINS:3dimage/io
srcz = (required, io)
Study image Z-tag. For supported file types see PLUGINS:3dimage/io
weight = 1 (float)
weight of cost function. in [-1e+10, 1e+10]
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:
unsigned 16 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
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:
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
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
rot-center = [[0,0,0]] (streamable)
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
rot-center = [[0,0,0]] (streamable)
Relative rotation center, i.e. <0.5,0.5,0.5> corresponds to the center of
the volume.
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)
isotropic coefficient rate in pixels. in [1, 3.40282e+38]
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/splinepenalty
divcurl divcurl penalty on the transformation, supported parameters are:
curl = 1 (float)
penalty weight on curl. in [0, 3.40282e+38]
div = 1 (float)
penalty weight on divergence. in [0, 3.40282e+38]
weight = 1 (float)
weight of penalty energy. in [0, 3.40282e+38]
PLUGINS: minimizer/singlecost
gdsq Gradient descent with quadratic step estimation, supported parameters are:
ftolr = 0 (double)
Stop if the relative change of the criterion is below.. in [0, INF]
gtola = 0 (double)
Stop if the inf-norm of the gradient is below this value.. in [0, INF]
maxiter = 100 (uint)
Stopping criterion: the maximum number of iterations. in [1, 2147483647]
scale = 2 (double)
Fallback fixed step size scaling. in [1, INF]
step = 0.1 (double)
Initial step size. in [0, INF]
xtola = 0 (double)
Stop if the inf-norm of x-update is below this value.. in [0, INF]
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)
gradient based optimizers: stop when |grad| < eps, simplex: stop when
simplex size < eps.. in [1e-10, 10]
iter = 100 (int)
maximum number of iterations. in [1, 2147483647]
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)
initial step size. in [0, 10]
tol = 0.1 (double)
some tolerance parameter. in [0.001, 10]
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)
Stopping criterion: the absolute change of the objective value is below
this value. in [0, INF]
ftolr = 0 (double)
Stopping criterion: the relative change of the objective value is below
this value. in [0, INF]
higher = inf (double)
Higher boundary (equal for all parameters). in [INF, INF]
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). in [INF, INF]
maxiter = 100 (int)
Stopping criterion: the maximum number of iterations. in [1, 2147483647]
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)
Initial step size for gradient free methods. in [0, INF]
stop = -inf (double)
Stopping criterion: function value falls below this value. in [INF, INF]
xtola = 0 (double)
Stopping criterion: the absolute change of all x-values is below this
value. in [0, INF]
xtolr = 0 (double)
Stopping criterion: the relative change of all x-values is below this
value. in [0, INF]
EXAMPLE
Register the image series given by images imageXXXX.v by optimizing a spline based
transformation with a coefficient rate of 16 pixel, skipping two images at the beginning
and using normalized gradient fields as initial cost measure and SSD as final measure.
Penalize the transformation by using divcurl with aweight of 2.0. As optimizer an nlopt
based newton method is used.
mia-3dprealign-nonrigid mia-3dprealign-nonrigid -i imageXXXX.v -o registered -t vista -k
2-F spline:rate=16,penalty=[divcurl:weight=2] -1 image:cost=[ngf:eval=ds] -2
image:cost=ssd -O nlopt:opt=ld-var1,xtola=0.001,ftolr=0.001,maxiter=300
AUTHOR(s)
Gert Wollny
COPYRIGHT
This software is Copyright (c) 1999‐2013 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'.