Provided by: mia-tools_2.0.13-1_amd64 bug

NAME

       mia-2dmyoperiodic-nonrigid - Run a registration of a series of 2D images.

SYNOPSIS

       mia-2dmyoperiodic-nonrigid -i <in-file> -o <out-file> [options]

DESCRIPTION

       mia-2dmyoperiodic-nonrigid  This  program  runs  the  non-rigid registration of an perfusion image series
       preferable acquired letting the patient breath freely. The registration algorithm implementes 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 perfusion data set

              -o --out-file=(required)
                     output perfusion data set

              -r --registered=reg
                     file name base for registered fiels

                 --save-references
                     Save synthetic references to files refXXXX.v

   Preconditions
              -k --skip=0
                     Skip images at the begin of the series

                 --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:2dimage/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

              -R --refiner=
                     optimizer    used    for    additional    minimization     For    supported   plugins   see
                     PLUGINS:minimizer/singlecost

              -l --mr-levels=3
                     multi-resolution levels

              -f --transForm=spline:rate=16,penalty=[divcurl:weight=0.01]
                     transformation type  For supported plugins see PLUGINS:2dimage/transform

              -1 --cost-subset=image:cost=[ngf:eval=ds]
                     Cost function for registration during the subset registration  For  supported  plugins  see
                     PLUGINS:2dimage/fullcost

              -2 --cost-final=image:cost=ssd
                     Cost  function  for  registration  during the final registration  For supported plugins see
                     PLUGINS:2dimage/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: 2dimage/cost

       lsd       Least-Squares Distance measure

                     (no parameters)

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

                     cut = 0 (float)
                       Percentage of pixels to cut at high and low intensities to remove outliers.  in [0, 40]

                     mbins = 64 (uint)
                       Number of histogram bins used for the moving image.  in [1, 256]

                     mkernel = [bspline:d=3] (factory)
                       Spline  kernel  for  moving  image  parzen  hinstogram.   For  supported   plug-ins   see
                       PLUGINS:1d/splinekernel

                     rbins = 64 (uint)
                       Number of histogram bins used for the reference image.  in [1, 256]

                     rkernel = [bspline:d=0] (factory)
                       Spline  kernel  for  reference  image  parzen  hinstogram.   For  supported  plug-ins see
                       PLUGINS:1d/splinekernel

       ngf       This function evaluates the image similarity  based  on  normalized  gradient  fields.  Various
                 evaluation kernels are availabe., supported parameters are:

                     eval = ds (string)
                       plugin subtype (sq, ds,dot,cross).

       ssd       2D imaga cost: sum of squared differences, supported parameters are:

                     norm = 0 (bool)
                       Set whether the metric should be normalized by the number of image pixels.

PLUGINS: 2dimage/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 (factory)
                       Cost function kernel.  For supported plug-ins see PLUGINS:2dimage/cost

                     debug = 0 (bool)
                       Save intermediate resuts for debugging.

                     ref = ref.@ (io)
                       Reference image.  For supported file types see PLUGINS:2dimage/io

                     src = src.@ (io)
                       Study image.  For supported file types see PLUGINS:2dimage/io

                     weight = 1 (float)
                       weight of cost function.  in [-1e+10, 1e+10]

PLUGINS: 2dimage/io

       bmp       BMP 2D-image input/output support

                     Recognized file extensions:  .BMP, .bmp

                     Supported element types:
                       binary data, unsigned 8 bit, unsigned 16 bit

       datapool  Virtual IO to and from the internal data pool

                     Recognized file extensions:  .@

       dicom     2D image io for DICOM

                     Recognized file extensions:  .DCM, .dcm

                     Supported element types:
                       unsigned 16 bit

       exr       a 2dimage io plugin for OpenEXR images

                     Recognized file extensions:  .EXR, .exr

                     Supported element types:
                       unsigned 32 bit, floating point 32 bit

       jpg       a 2dimage io plugin for jpeg gray scale images

                     Recognized file extensions:  .JPEG, .JPG, .jpeg, .jpg

                     Supported element types:
                       unsigned 8 bit

       png       a 2dimage io plugin for png images

                     Recognized file extensions:  .PNG, .png

                     Supported element types:
                       binary data, unsigned 8 bit, unsigned 16 bit

       raw       RAW 2D-image output support

                     Recognized file extensions:  .RAW, .raw

                     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

       tif       TIFF 2D-image input/output support

                     Recognized file extensions:  .TIF, .TIFF, .tif, .tiff

                     Supported element types:
                       binary data, unsigned 8 bit, unsigned 16 bit, unsigned 32 bit

       vista     a 2dimage io plugin for vista images

                     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

PLUGINS: 2dimage/transform

       affine    Affine transformation (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

       rigid     Rigid transformations (i.e. rotation and 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

                     rot-center = [[0,0]] (streamable)
                       Relative  rotation  center,  i.e.   <0.5,0.5>  corresponds  to  the center of the support
                       rectangle.

       rotation  Rotation transformations (i.e.  rotation  about  a  given  center,  one  degree  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]] (streamable)
                       Relative  rotation  center,  i.e.   <0.5,0.5>  corresponds  to  the center of the support
                       rectangle.

       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]] (2dfvector)
                       anisotropic  coefficient  rate  in  pixels, nonpositive values will be overwritten by the
                       'rate' value..

                     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      term.       For       supported       plug-ins       see
                       PLUGINS:2dtransform/splinepenalty

                     rate = 10 (float)
                       isotropic coefficient rate in pixels.  in [1, 3.40282e+38]

       translate Translation only (two 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: 2dtransform/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  perfusion  series  given  in  'segment.set'.  Skip two images at the beginning, usa spline
       transformation of a knot rate 16 pixels, and penalize the transformation by divcurl with weight 5.  Store
       the result in 'registered.set'.

       mia-2dmyoperiodic-nonrigid       -i     segment.set     -o     registered.set    -k    2    -d    5    -f
              spline:rate=16,penalty=[divcurl:weight=5]

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'.

2.0.10                                           25 January 2014                   mia-2dmyoperiodic-nonrigid(1)