Provided by: mia-tools_2.4.6-5build3_amd64 bug

NAME

       mia-3dnonrigidreg - Non-linear registration of 3D images

SYNOPSIS

       mia-3dnonrigidreg -i <in-image> -r <ref-image> -o <out-image> [options] <PLUGINS:3dimage/fullcost>

DESCRIPTION

       mia-3dnonrigidreg This program implements the registration of two gray scale 3D images.

OPTIONS

   Help & Info
              -V --verbose=warning
                     verbosity  of  output,  print  messages  of  given  level  and higher priorities. Supported
                     priorities starting at lowest level are:

                        trace ‐ Function call trace
                        debug ‐ Debug output
                        info ‐ Low level messages
                        message ‐ Normal messages
                        warning ‐ Warnings
                        fail ‐ Report test failures
                        error ‐ Report errors
                        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

   IO
              -i --in-image=(required, input); io
                     test image
                      For supported file types see PLUGINS:3dimage/io

              -r --ref-image=(required, input); io
                     reference image
                      For supported file types see PLUGINS:3dimage/io

              -o --out-image=(required, output); io
                     registered output image
                      For supported file types see PLUGINS:3dimage/io

              -t --transformation=(output); io
                     output transformation
                      For supported file types see PLUGINS:3dtransform/io

   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).

   Registration
              -l --levels=3
                     multi-resolution levels

              -O --optimizer=gsl:opt=gd,step=0.1
                     Optimizer used for minimization
                      For supported plugins see PLUGINS:minimizer/singlecost

              -f --transForm=spline:rate=10
                     transformation type
                      For supported plugins see PLUGINS:3dimage/transform

PLUGINS: 1d/spacialkernel

       cdiff     Central difference filter kernel, mirror boundary conditions are used.

                     (no parameters)

       gauss     spacial Gauss filter kernel, supported parameters are:

                     w = 1; uint in [0, inf)
                       half filter width.

       scharr    This plugin provides the 1D folding kernel for the Scharr gradient filter

                     (no parameters)

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/combiner

       absdiff   Image combiner 'absdiff'

                     (no parameters)

       add       Image combiner 'add'

                     (no parameters)

       div       Image combiner 'div'

                     (no parameters)

       mul       Image combiner 'mul'

                     (no parameters)

       sub       Image combiner 'sub'

                     (no parameters)

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/filter

       bandpass  intensity bandpass filter, supported parameters are:

                     max = 3.40282e+38; float
                       maximum of the band.

                     min = 0; float
                       minimum of the band.

       binarize  image binarize filter, supported parameters are:

                     max = 3.40282e+38; float
                       maximum of accepted range.

                     min = 0; float
                       minimum of accepted range.

       close     morphological close, supported parameters are:

                     hint = black; string
                       a hint at the main image content (black|white).

                     shape = [sphere:r=2]; factory
                       structuring element.  For supported plug-ins see PLUGINS:3dimage/shape

       combiner  Combine  two  images  with the given combiner operator. if 'reverse' is set to false, the first
                 operator is the image passed through the filter pipeline, and the second image is  loaded  from
                 the  file  given with the 'image' parameter the moment the filter is run., supported parameters
                 are:

                     image =(required, input, io)
                       second  image  that  is  needed  in  the  combiner.   For  supported   file   types   see
                       PLUGINS:3dimage/io

                     op =(required, factory)
                       Image   combiner   to   be   applied   to   the   images.   For  supported  plug-ins  see
                       PLUGINS:3dimage/combiner

                     reverse = 0; bool
                       reverse the order in which the images passed to the combiner.

       convert   image pixel format conversion filter, supported parameters are:

                     a = 1; float
                       linear conversion parameter a.

                     b = 0; float
                       linear conversion parameter b.

                     map = opt; dict
                       conversion mapping.  Supported values are:
                           copy ‐ copy data when converting
                           linear ‐ apply linear transformation x -> a*x+b
                           range ‐ apply linear transformation that maps the input data type range to the output
                           data type range
                           opt ‐ apply a linear transformation that maps the real input range to the full output
                           range
                           optstat ‐ apply a linear transform that maps based on input mean and variation to the
                           full output range

                     repn = ubyte; dict
                       output pixel type.  Supported values are:
                           bit ‐ binary data
                           sbyte ‐ signed 8 bit
                           ubyte ‐ unsigned 8 bit
                           sshort ‐ signed 16 bit
                           ushort ‐ unsigned 16 bit
                           sint ‐ signed 32 bit
                           uint ‐ unsigned 32 bit
                           slong ‐ signed 64 bit
                           ulong ‐ unsigned 64 bit
                           float ‐ floating point 32 bit
                           double ‐ floating point 64 bit
                           none ‐ no pixel type defined

       crop      Crop a region of an image, the region is always clamped to the original image size in the sense
                 that the given range is kept., supported parameters are:

                     end = [[4294967295,4294967295,4294967295]]; streamable
                       end of cropping range, maximum = (-1,-1,-1).

                     start = [[0,0,0]]; streamable
                       begin of cropping range.

       dilate    3d image stack dilate filter, supported parameters are:

                     hint = black; string
                       a hint at the main image content (black|white).

                     shape = [sphere:r=2]; factory
                       structuring element.  For supported plug-ins see PLUGINS:3dimage/shape

       distance  Evaluate the 3D distance transform of an image. If the image is a binary mask, then  result  of
                 the  distance transform in each point corresponds to the Euclidian distance to the mask. If the
                 input image is of a scalar pixel value, then the this scalar is interpreted as  heighfield  and
                 the per pixel value adds to the distance.

                     (no parameters)

       downscale Downscale  the input image by using a given block size to define the downscale factor. Prior to
                 scaling the image is filtered by a smoothing filter to eliminate high frequency data and  avoid
                 aliasing artifacts., supported parameters are:

                     b = [[1,1,1]]; 3dbounds
                       blocksize.

                     bx = 1; uint in [1, inf)
                       blocksize in x direction.

                     by = 1; uint in [1, inf)
                       blocksize in y direction.

                     bz = 1; uint in [1, inf)
                       blocksize in z direction.

                     kernel = gauss; factory
                       smoothing  filter  kernel to be applied, the size of the filter is estimated based on the
                       blocksize..  For supported plug-ins see PLUGINS:1d/spacialkernel

       erode     3d image stack erode filter, supported parameters are:

                     hint = black; string
                       a hint at the main image content (black|white).

                     shape = [sphere:r=2]; factory
                       structuring element.  For supported plug-ins see PLUGINS:3dimage/shape

       gauss     isotropic 3D gauss filter, supported parameters are:

                     w = 1; int in [0, inf)
                       filter width parameter.

       gradnorm  3D image to gradient norm filter

                     (no parameters)

       growmask  Use an input binary mask and a reference gray scale image to do region growing  by  adding  the
                 neighborhood  pixels  of an already added pixel if the have a lower intensity that is above the
                 given threshold., supported parameters are:

                     min = 1; float
                       lower threshold for mask growing.

                     ref =(required, input, io)
                       reference image for mask region growing.  For supported file types see PLUGINS:3dimage/io

                     shape = 6n; factory
                       neighborhood mask.  For supported plug-ins see PLUGINS:3dimage/shape

       invert    intensity invert filter

                     (no parameters)

       isovoxel  This filter scales an image to make the voxel size isometric and its size to correspond to  the
                 given value, supported parameters are:

                     interp = [bspline:d=3]; factory
                       interpolation kernel to be used .  For supported plug-ins see PLUGINS:1d/splinekernel

                     size = 1; float in (0, inf)
                       isometric target voxel size.

       kmeans    3D  image  k-means  filter. In the output image the pixel value represents the class membership
                 and the class centers are stored as attribute in the image., supported parameters are:

                     c = 3; int in [2, inf)
                       number of classes.

       label     A filter to label the  connected components of a binary image., supported parameters are:

                     n = 6n; factory
                       neighborhood mask.  For supported plug-ins see PLUGINS:3dimage/shape

       labelmap  Image  filter  to  remap  label  id's.  Only  applicable  to   images   with   integer   valued
                 intensities/labels., supported parameters are:

                     map =(required, input, string)
                       Label mapping file.

       labelscale
                 A  filter  that only creates output voxels that are already created in the input image. Scaling
                 is done by using a voting algorithms that selects the target pixel value based on  the  highest
                 pixel  count of a certain label in the corresponding source region. If the region comprises two
                 labels with the same count, the one with the lower number wins., supported parameters are:

                     out-size =(required, 3dbounds)
                       target size given as two coma separated values.

       load      Load the input image from a file and use it to replace the  current  image  in  the  pipeline.,
                 supported parameters are:

                     file =(required, input, io)
                       name of the input file to load from..  For supported file types see PLUGINS:3dimage/io

       lvdownscale
                 This  is  a  label voting downscale filter. It adownscales a 3D image by blocks. For each block
                 the (non-zero) label that appears most times in the block is issued  as  output  pixel  in  the
                 target  image.  If  two labels appear the same number of times, the one with the lower absolute
                 value wins., supported parameters are:

                     b = [[1,1,1]]; 3dbounds
                       blocksize for the downscaling. Each block will be represented by one pixel in the  target
                       image..

       mask      Mask an image, one image is taken from the parameters list and the other from the normal filter
                 input. Both images must be of the same dimensions and one must be binary. The attributes of the
                 image  coming  through  the filter pipeline are preserved. The output pixel type corresponds to
                 the input image that is not binary., supported parameters are:

                     input =(required, input, io)
                       second input image file name.  For supported file types see PLUGINS:3dimage/io

       mean      3D image mean filter, supported parameters are:

                     w = 1; int in [1, inf)
                       half filter width.

       median    median 3d filter, supported parameters are:

                     w = 1; int in [1, inf)
                       filter width parameter.

       mlv       Mean of Least Variance 3D image filter, supported parameters are:

                     w = 1; int in [1, inf)
                       filter width parameter.

       msnormalizer
                 3D image mean-sigma normalizing filter, supported parameters are:

                     w = 1; int in [1, inf)
                       half filter width.

       open      morphological open, supported parameters are:

                     hint = black; string
                       a hint at the main image content (black|white).

                     shape = [sphere:r=2]; factory
                       structuring element.  For supported plug-ins see PLUGINS:3dimage/shape

       reorient  3D image reorientation filter, supported parameters are:

                     map = xyz; dict
                       oriantation mapping to be applied.  Supported values are:
                           xyz ‐ keep orientation
                           p-yzx ‐ permutate x->z->y->x
                           p-zxy ‐ permutate x->y->z->x
                           f-yz ‐ flip y-z
                           f-xy ‐ flip x-y
                           f-xz ‐ flip x-z
                           r-x90 ‐ rotate around x-axis clockwise 90 degree
                           r-x180 ‐ rotate around x-axis clockwise 180 degree
                           r-x270 ‐ rotate around x-axis clockwise 270 degree
                           r-y90 ‐ rotate around y-axis clockwise 90 degree
                           r-y180 ‐ rotate around y-axis clockwise 180 degree
                           r-y270 ‐ rotate around y-axis clockwise 270 degree
                           r-z90 ‐ rotate around z-axis clockwise 90 degree
                           r-z180 ‐ rotate around z-axis clockwise 180 degree
                           r-z270 ‐ rotate around z-axis clockwise 270 degree

       resize    Resize an image. The  original  data  is  centered  within  the  new  sized  image.,  supported
                 parameters are:

                     size = [[0,0,0]]; streamable
                       new  size  of  the  image  a  size  0  indicates  to  keep the size for the corresponding
                       dimension..

       sandp     salt and pepper  3d filter, supported parameters are:

                     thresh = 100; float in [0, inf)
                       thresh value.

                     w = 1; int in [1, inf)
                       filter width parameter.

       scale     3D image filter that scales to a given target size , supported parameters are:

                     interp = [bspline:d=3]; factory
                       interpolation kernel to be used .  For supported plug-ins see PLUGINS:1d/splinekernel

                     s = [[0,0,0]]; 3dbounds
                       target size to set all components at once (component 0:use input image size).

                     sx = 0; uint in [0, inf)
                       target size in x direction (0:use input image size).

                     sy = 0; uint in [0, inf)
                       target size in y direction (0:use input image size).

                     sz = 0; uint in [0, inf)
                       target size in y direction (0:use input image size).

       scharr    The 3D Scharr filter for gradient evaluation. Note that the output pixel type of  the  filtered
                 image  is  the  same  as the input pixel type, so converting the input beforehand to a floating
                 point valued image is recommendable., supported parameters are:

                     dir = x; dict
                       Gradient direction.  Supported values are:
                           x ‐ gradient in x-direction
                           y ‐ gradient in y-direction
                           z ‐ gradient in z-direction

       selectbig A filter that creats a binary mask representing the intensity with the highest pixel  count.The
                 pixel  value  0  will  be  ignored,  and if two intensities have the same pixel count, then the
                 result is undefined. The input pixel must have an integral pixel type.

                     (no parameters)

       sepconv   3D image intensity separaple convolution filter, supported parameters are:

                     kx = [gauss:w=1]; factory
                       filter kernel in x-direction.  For supported plug-ins see PLUGINS:1d/spacialkernel

                     ky = [gauss:w=1]; factory
                       filter kernel in y-direction.  For supported plug-ins see PLUGINS:1d/spacialkernel

                     kz = [gauss:w=1]; factory
                       filter kernel in z-direction.  For supported plug-ins see PLUGINS:1d/spacialkernel

       sobel     The 2D Sobel filter for gradient evaluation. Note that the output pixel type  of  the  filtered
                 image  is  the  same  as the input pixel type, so converting the input beforehand to a floating
                 point valued image is recommendable., supported parameters are:

                     dir = x; dict
                       Gradient direction.  Supported values are:
                           x ‐ gradient in x-direction
                           y ‐ gradient in y-direction
                           z ‐ gradient in z-direction

       sws       seeded watershead. The algorithm extracts exactly so many reagions as initial labels are  given
                 in the seed image., supported parameters are:

                     grad = 0; bool
                       Interpret the input image as gradient. .

                     mark = 0; bool
                       Mark the segmented watersheds with a special gray scale value.

                     n = [sphere:r=1]; factory
                       Neighborhood    for    watershead   region   growing.    For   supported   plug-ins   see
                       PLUGINS:3dimage/shape

                     seed =(required, input, string)
                       seed input image containing the lables for the initial regions.

       tee       Save the input image to a file  and  also  pass  it  through  to  the  next  filter,  supported
                 parameters are:

                     file =(required, output, io)
                       name  of  the  output  file  to  save  the  image  too..   For  supported  file types see
                       PLUGINS:3dimage/io

       thinning  3D morphological thinning,  based on: Lee and Kashyap, 'Building Skeleton Models via 3-D Medial
                 Surface/Axis  Thinning Algorithms', Graphical Models and Image Processing, 56(6):462-478, 1994.
                 This implementation only supports the 26 neighbourhood.

                     (no parameters)

       transform Transform the input image with the given transformation., supported parameters are:

                     file =(required, input, io)
                       Name  of  the  file  containing  the  transformation..   For  supported  file  types  see
                       PLUGINS:3dtransform/io

                     imgboundary = ; factory
                       override   image   interpolation   boundary   conditions.   For  supported  plug-ins  see
                       PLUGINS:1d/splinebc

                     imgkernel = ; factory
                       override image interpolator kernel.  For supported plug-ins see PLUGINS:1d/splinekernel

       variance  3D image variance filter, supported parameters are:

                     w = 1; int in [1, inf)
                       half filter width.

       ws        basic watershead segmentation., supported parameters are:

                     evalgrad = 0; bool
                       Set to 1 if the input image does not represent a gradient norm image.

                     mark = 0; bool
                       Mark the segmented watersheds with a special gray scale value.

                     n = [sphere:r=1]; factory
                       Neighborhood   for   watershead   region   growing.    For   supported    plug-ins    see
                       PLUGINS:3dimage/shape

                     thresh = 0; float in [0, 1)
                       Relative  gradient norm threshold. The actual value threshold value is thresh * (max_grad
                       - min_grad) + min_grad. Bassins separated by gradients with a lower norm will be joined.

PLUGINS: 3dimage/fullcost

       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:3dimage/cost

                     debug = 0; bool
                       Save intermediate resuts for debugging.

                     ref =(input, io)
                       Reference image.  For supported file types see PLUGINS:3dimage/io

                     src =(input, io)
                       Study image.  For supported file types see PLUGINS:3dimage/io

                     weight = 1; float
                       weight of cost function.

       labelimage
                 Similarity  cost  function  that  maps labels of two images and handles label-preserving multi-
                 resolution processing., supported parameters are:

                     maxlabel = 256; int in [2, 32000]
                       maximum number of labels to consider.

                     ref =(input, io)
                       Reference image.  For supported file types see PLUGINS:3dimage/io

                     src =(input, io)
                       Study image.  For supported file types see PLUGINS:3dimage/io

                     weight = 1; float
                       weight of cost function.

       maskedimage
                 Generalized  masked  image  similarity  cost  function  that  also   handles   multi-resolution
                 processing.  The  provided  masks should be densly filled regions in multi-resolution procesing
                 because otherwise the mask information may get lost when downscaling the image. The mask may be
                 pre-filtered  -  after  pre-filtering  the masks must be of bit-type.The reference mask and the
                 transformed mask of the study image are combined by binary AND. The actual  similarity  measure
                 is given es extra parameter., supported parameters are:

                     cost = ssd; factory
                       Cost function kernel.  For supported plug-ins see PLUGINS:3dimage/maskedcost

                     ref =(input, io)
                       Reference image.  For supported file types see PLUGINS:3dimage/io

                     ref-mask =(input, io)
                       Reference image mask  (binary).  For supported file types see PLUGINS:3dimage/io

                     ref-mask-filter = ; factory
                       Filter  to  prepare  the  reference  mask image, the output must be a binary image..  For
                       supported plug-ins see PLUGINS:3dimage/filter

                     src =(input, io)
                       Study image.  For supported file types see PLUGINS:3dimage/io

                     src-mask =(input, io)
                       Study image mask (binary).  For supported file types see PLUGINS:3dimage/io

                     src-mask-filter = ; factory
                       Filter to prepare the study mask  image,  the  output  must  be  a  binary  image..   For
                       supported plug-ins see PLUGINS:3dimage/filter

                     weight = 1; float
                       weight of cost function.

       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 =(input, io)
                       Reference image  X-tag.  For supported file types see PLUGINS:3dimage/io

                     refy =(input, io)
                       Reference image  Y-tag.  For supported file types see PLUGINS:3dimage/io

                     refz =(input, io)
                       Reference image  Z-tag.  For supported file types see PLUGINS:3dimage/io

                     srcx =(input, io)
                       Study image X-tag.  For supported file types see PLUGINS:3dimage/io

                     srcy =(input, io)
                       Study image Y-tag.  For supported file types see PLUGINS:3dimage/io

                     srcz =(input, io)
                       Study image Z-tag.  For supported file types see PLUGINS:3dimage/io

                     weight = 1; float
                       weight of cost function.

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. The orientation is transformed in the  same  way  like  it  is  done  with
                 'dicomtonifti --no-reorder' from the vtk-dicom package.

                     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:
                       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/maskedcost

       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 with masking., 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 with masking support.

                     (no parameters)

       ssd       Sum of squared differences with masking.

                     (no parameters)

PLUGINS: 3dimage/shape

       18n       18n neighborhood 3D shape creator

                     (no parameters)

       26n       26n neighborhood 3D shape creator

                     (no parameters)

       6n        6n neighborhood 3D shape creator

                     (no parameters)

       sphere    Closed  spherical  shape  neighborhood including the pixels within a given radius r., supported
                 parameters are:

                     r = 2; float in (0, inf)
                       sphere radius.

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 debugging 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  of  the  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:
                           simplex ‐ Simplex algorithm of Nelder and Mead
                           cg-fr ‐ Flecher-Reeves conjugate gradient algorithm
                           cg-pr ‐ Polak-Ribiere conjugate gradient algorithm
                           bfgs ‐ Broyden-Fletcher-Goldfarb-Shann
                           bfgs2 ‐ Broyden-Fletcher-Goldfarb-Shann (most efficient version)
                           gd ‐ Gradient descent.

                     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-direct ‐ Dividing Rectangles
                           gn-direct-l ‐ Dividing Rectangles (locally biased)
                           gn-direct-l-rand ‐ Dividing Rectangles (locally biased, randomized)
                           gn-direct-noscal ‐ Dividing Rectangles (unscaled)
                           gn-direct-l-noscal ‐ Dividing Rectangles (unscaled, locally biased)
                           gn-direct-l-rand-noscale ‐ Dividing Rectangles (unscaled, locally biased, randomized)
                           gn-orig-direct ‐ Dividing Rectangles (original implementation)
                           gn-orig-direct-l ‐ Dividing Rectangles (original implementation, locally biased)
                           ld-lbfgs-nocedal ‐ None
                           ld-lbfgs ‐ Low-storage BFGS
                           ln-praxis ‐ Gradient-free Local Optimization via the Principal-Axis Method
                           ld-var1 ‐ Shifted Limited-Memory Variable-Metric, Rank 1
                           ld-var2 ‐ Shifted Limited-Memory Variable-Metric, Rank 2
                           ld-tnewton ‐ Truncated Newton
                           ld-tnewton-restart ‐ Truncated Newton with steepest-descent restarting
                           ld-tnewton-precond ‐ Preconditioned Truncated Newton
                           ld-tnewton-precond-restart  ‐  Preconditioned  Truncated Newton with steepest-descent
                           restarting
                           gn-crs2-lm ‐ Controlled Random Search with Local Mutation
                           ld-mma ‐ Method of Moving Asymptotes
                           ln-cobyla ‐ Constrained Optimization BY Linear Approximation
                           ln-newuoa ‐ Derivative-free Unconstrained  Optimization  by  Iteratively  Constructed
                           Quadratic Approximation
                           ln-newuoa-bound  ‐  Derivative-free  Bound-constrained  Optimization  by  Iteratively
                           Constructed Quadratic Approximation
                           ln-neldermead ‐ Nelder-Mead simplex algorithm
                           ln-sbplx ‐ Subplex variant of Nelder-Mead
                           ln-bobyqa ‐ Derivative-free Bound-constrained Optimization
                           gn-isres ‐ Improved Stochastic Ranking Evolution Strategy
                           none ‐ don't specify algorithm

                     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-direct ‐ Dividing Rectangles
                           gn-direct-l ‐ Dividing Rectangles (locally biased)
                           gn-direct-l-rand ‐ Dividing Rectangles (locally biased, randomized)
                           gn-direct-noscal ‐ Dividing Rectangles (unscaled)
                           gn-direct-l-noscal ‐ Dividing Rectangles (unscaled, locally biased)
                           gn-direct-l-rand-noscale ‐ Dividing Rectangles (unscaled, locally biased, randomized)
                           gn-orig-direct ‐ Dividing Rectangles (original implementation)
                           gn-orig-direct-l ‐ Dividing Rectangles (original implementation, locally biased)
                           ld-lbfgs-nocedal ‐ None
                           ld-lbfgs ‐ Low-storage BFGS
                           ln-praxis ‐ Gradient-free Local Optimization via the Principal-Axis Method
                           ld-var1 ‐ Shifted Limited-Memory Variable-Metric, Rank 1
                           ld-var2 ‐ Shifted Limited-Memory Variable-Metric, Rank 2
                           ld-tnewton ‐ Truncated Newton
                           ld-tnewton-restart ‐ Truncated Newton with steepest-descent restarting
                           ld-tnewton-precond ‐ Preconditioned Truncated Newton
                           ld-tnewton-precond-restart ‐ Preconditioned Truncated  Newton  with  steepest-descent
                           restarting
                           gn-crs2-lm ‐ Controlled Random Search with Local Mutation
                           ld-mma ‐ Method of Moving Asymptotes
                           ln-cobyla ‐ Constrained Optimization BY Linear Approximation
                           ln-newuoa  ‐  Derivative-free  Unconstrained  Optimization by Iteratively Constructed
                           Quadratic Approximation
                           ln-newuoa-bound  ‐  Derivative-free  Bound-constrained  Optimization  by  Iteratively
                           Constructed Quadratic Approximation
                           ln-neldermead ‐ Nelder-Mead simplex algorithm
                           ln-sbplx ‐ Subplex variant of Nelder-Mead
                           ln-bobyqa ‐ Derivative-free Bound-constrained Optimization
                           gn-isres ‐ Improved Stochastic Ranking Evolution Strategy
                           auglag ‐ Augmented Lagrangian algorithm
                           auglag-eq ‐ Augmented Lagrangian algorithm with equality constraints only
                           g-mlsl ‐ Multi-Level Single-Linkage (require local optimization and bounds)
                           g-mlsl-lds  ‐  Multi-Level  Single-Linkage  (low-discrepancy-sequence,  require local
                           gradient based optimization and bounds)
                           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 by using a spline transformation with a coefficient rate of  5   and
       write  the  registered  image  to  reg.v.  Use two multiresolution levels, ssd as image cost function and
       divcurl weighted by 10.0 as transformation smoothness penalty.

       mia-3dnonrigidreg -i test.v -r ref.v -o reg.v -l 2 -f spline:rate=3  image:cost=ssd divcurl:weight=10

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'.