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

NAME

       mia-2dseries2dordermedian  -  Evaluate  time-intensity  median  2nd  order derivative of a
       series.

SYNOPSIS

       mia-2dseries2dordermedian -i <in-file> -o <out-file> [options] <PLUGINS:2dimage/filter>

DESCRIPTION

       mia-2dseries2dordermedian This program evaluates the pixel-wise  median  of  the  absolute
       values  of  the  gauss  filtered  2nd  order temporal derivative of a series of images. In
       addition, it can be used to output the time-intensity curve of a given  pixel.The  program
       supports  slice-wise spacial pre-filtering by giving additional filters as free parameters
       (filter/2dimage).

OPTIONS

              -i --in-file=(required)
                     input segmentation set

              -o --out-file=(required)
                     output image name  For supported file types see PLUGINS:2dimage/io

              -k --skip=0
                     Skip files at the beginning

              -e --enlarge-boundary=5
                     Enlarge cropbox by number of pixels

              -c --crop
                     crop image before running statistics

              -g --gauss=1
                     gauss filter width for moothing the gradient

                 --itc-file=
                     intensity time curve output file

                 --itc-loc=[0,0]
                     intensity time curve output pixel coordinates

   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/spacialkernel

       gauss     spacial Gauss filter kernel, supported parameters are:

                     w = 1 (int)
                       half filter width.  in [0, 2147483647]

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/filter

       adaptmed  2D image adaptive median filter, supported parameters are:

                     w = 2 (int)
                       half filter width.  in [0, 2147483647]

       admean    An  adaptive  mean filter that works like a normal mean filter, if the intensity
                 variation within the filter mask is lower then the intensity  variation  in  the
                 whole  image,  that  the uses a special formula if the local variation is higher
                 then the image intensity variation., supported parameters are:

                     w = 1 (int)
                       half filter width.  in [0, 2147483647]

       aniso     2D Anisotropic image filter, supported parameters are:

                     epsilon = 1 (float)
                       iteration change threshold.  in [0.001, 100]

                     iter = 100 (int)
                       number of iterations.  in [1, 10000]

                     k = -1 (float)
                       k the noise threshold (<=0 -> adaptive).  in [0, 100]

                     n = 8 (set)
                       neighbourhood.  Supported values are:( 4,  8,  )

                     psi = tuckey (dict)
                       edge stopping function.  Supported values are:
                           guess ‐ test stopping function
                           tuckey ‐ tukey stopping function
                           pm1 ‐ stopping function 1
                           pm2 ‐ stopping function 2

       bandpass  intensity bandpass filter, supported parameters are:

                     max = 3.40282e+38 (float)
                       maximum of the band.  in [-3.40282e+38, 3.40282e+38]

                     min = 0 (float)
                       minimum of the band.  in [-3.40282e+38, 3.40282e+38]

       binarize  image binarize filter, supported parameters are:

                     max = 3.40282e+38 (float)
                       maximum of accepted range.  in [0, 3.40282e+38]

                     min = 0 (float)
                       minimum of accepted range.  in [0, 3.40282e+38]

       close     morphological close, supported parameters are:

                     hint = black (set)
                       a hint at the main image content.  Supported values are:(  black,   white,
                       )

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

       convert   image pixel format conversion filter, supported parameters are:

                     a = 1 (float)
                       linear conversion parameter a.  in [-3.40282e+38, 3.40282e+38]

                     b = 0 (float)
                       linear conversion parameter b.  in [-3.40282e+38, 3.40282e+38]

                     map = opt (dict)
                       conversion mapping.  Supported values are:
                           opt  ‐ apply a linear transformation that maps the real input range to
                           the full output range
                           range ‐ apply linear transformation that  maps  the  input  data  type
                           range to the output data type range
                           copy ‐ copy data when converting
                           linear ‐ apply linear transformation x -> a*x+b
                           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:
                           float ‐ floating point 32 bit
                           sbyte ‐ signed 8 bit
                           ulong ‐ unsigned 64 bit
                           double ‐ floating point 64 bit
                           sint ‐ signed 32 bit
                           ushort ‐ unsigned 16 bit
                           sshort ‐ signed 16 bit
                           uint ‐ unsigned 32 bit
                           slong ‐ signed 64 bit
                           bit ‐ binary data
                           ubyte ‐ unsigned 8 bit

       crop      Crop a region of an image, the region is always clamped to  the  original  image
                 size., supported parameters are:

                     end = [[-1,-1]] (streamable)
                       end of crop region.

                     start = [[0,0]] (streamable)
                       start of crop region.

       dilate    2d image stack dilate filter, supported parameters are:

                     hint = black (set)
                       a  hint  at the main image content.  Supported values are:( black,  white,
                       )

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

       distance  2D image distance filter, evaluates the distance map for a binary mask.

                     (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]] (2dbounds)
                       blocksize.

                     bx = 1 (uint)
                       blocksize in x direction.  in [1, 2147483647]

                     by = 1 (uint)
                       blocksize in y direction.  in [1, 2147483647]

                     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     2d image stack erode filter, supported parameters are:

                     hint = black (set)
                       a  hint  at the main image content.  Supported values are:( black,  white,
                       )

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

       gauss     isotropic 2D gauss filter, supported parameters are:

                     w = 1 (int)
                       filter width parameter.  in [0, 2147483647]

       gradnorm  2D image to gradient norm filter, supported parameters are:

                     normalize = 0 (bool)
                       Normalize the gradient norms to range [0,1]..

       invert    intensity invert filter

                     (no parameters)

       kmeans    2D 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)
                       number of classes.  in [2, 255]

       label     Label connected components in a binary 2D image., supported parameters are:

                     n = 4n (factory)
                       Neighborhood mask to describe connectivity..  For supported  plug-ins  see
                       PLUGINS:2dimage/shape

       labelmap  2D image filter to remap label id's., supported parameters are:

                     map = (required, string)
                       Label mapping file.

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

                     file = (required, io)
                       name of the input file to  load  from..   For  supported  file  types  see
                       PLUGINS:2dimage/io

       mask      2D  masking,  one  of  the  two  input  images  must  by of type bit., supported
                 parameters are:

                     fill = min (dict)
                       fill style for pixels outside of the mask.  Supported values are:
                           max ‐ set values outside the mask to the maximum value  found  in  the
                           image..
                           zero ‐ set the values outside the mask to zero.
                           min  ‐  set  values outside the mask to the minimum value found in the
                           image.

                     input = (required, io)
                       second  input  image  file   name.    For   supported   file   types   see
                       PLUGINS:2dimage/io

                     inverse = 0 (bool)
                       set to true to use the inverse of the mask for masking.

       mean      2D image mean filter, supported parameters are:

                     w = 0 (int)
                       half filter width.  in [0, 2147483647]

       median    2D image median filter, supported parameters are:

                     w = 0 (int)
                       half filter width.  in [0, 2147483647]

       mlv       Mean of Least Variance 2D image filter, supported parameters are:

                     w = 1 (int)
                       filter width parameter.  in [0, 2147483647]

       ngfnorm   2D image to normalized-gradiend-field-norm filter

                     (no parameters)

       noise     2D  image  noise  filter: add additive or modulated noise to an image, supported
                 parameters are:

                     g = [gauss:mu=0,sigma=10] (factory)
                       noise generator.  For supported plug-ins see PLUGINS:generator/noise

                     mod = 0 (bool)
                       additive or modulated noise.

       open      morphological open, supported parameters are:

                     hint = black (set)
                       a hint at the main image content.  Supported values are:(  black,   white,
                       )

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

       pruning   Morphological  pruning.  Pruning  until  convergence  will  erase all pixels but
                 closed loops., supported parameters are:

                     iter = 0 (int)
                       Number of iterations to run, 0=until convergence.  in [1, 1000000]

       regiongrow
                 Region growing startin from  a  seed  until  only  along  increasing  gradients,
                 supported parameters are:

                     n = 8n (factory)
                       Neighborhood shape.  For supported plug-ins see PLUGINS:2dimage/shape

                     seed = (required, io)
                       seed image (bit valued).  For supported file types see PLUGINS:2dimage/io

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

                     thresh = 100 (float)
                       thresh value.  in [0, 3.40282e+38]

                     w = 1 (int)
                       filter width parameter.  in [0, 2147483647]

       scale     2D image downscale filter, supported parameters are:

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

                     s = [[0,0]] (2dbounds)
                       target size as 2D vector.

                     sx = 0 (uint)
                       target size in x direction, 0: use input size.  in [0, 4294967295]

                     sy = 0 (uint)
                       target size in y direction, 0: use input size.  in [0, 4294967295]

       selectbig 2D label select biggest component filter

                     (no parameters)

       sepconv   2D 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

       shmean    2D image filter that  evaluates  the  mean  over  a  given  neighborhood  shape,
                 supported parameters are:

                     shape = 8n (factory)
                       neighborhood  shape  to  evaluate  the  mean.   For supported plug-ins see
                       PLUGINS:2dimage/shape

       sort-label
                 This plug-in sorts the labels of a gray-scale image so  that  the  lowest  label
                 value  corresponts  to  the lable with themost pixels. The background (0) is not
                 touched

                     (no parameters)

       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:2dimage/shape

                     seed = (required, 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, io)
                       name  of the output file to save the image too..  For supported file types
                       see PLUGINS:2dimage/io

       thinning  Morphological thinning. Thinning until convergence will result in a  8-connected
                 skeleton, supported parameters are:

                     iter = 0 (int)
                       Number of iterations to run, 0=until convergence.  in [1, 1000000]

       thresh    This  filter  sets  all  pixels  of  an  image to zero that fall below a certain
                 threshhold and whose neighbours in a given neighborhood shape also fall below  a
                 this threshhold, supported parameters are:

                     shape = 4n (factory)
                       neighborhood  shape  to  take  into  account.   For supported plug-ins see
                       PLUGINS:2dimage/shape

                     thresh = 5 (double)
                       The threshhold value.  in [-1.79769e+308, 1.79769e+308]

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

                     file = (required, io)
                       Name of the file containing the transformation..  For supported file types
                       see PLUGINS:2dtransform/io

       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:2dimage/shape

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

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/shape

       1n        A shape that only contains the central point

                     (no parameters)

       4n        4n neighborhood 2D shape

                     (no parameters)

       8n        8n neighborhood 2D shape

                     (no parameters)

       rectangle rectangle shape mask creator, supported parameters are:

                     fill = 1 (bool)
                       create a filled shape.

                     height = 2 (int)
                       height of rectangle.  in [0, 2147483647]

                     width = 2 (int)
                       width of rectangle.  in [0, 2147483647]

       sphere    Closed spherical neighborhood shape of radius r., supported parameters are:

                     r = 2 (float)
                       sphere radius.  in [0, 3.40282e+38]

       square    square shape mask creator, supported parameters are:

                     fill = 1 (bool)
                       create a filled shape.

                     width = 2 (int)
                       width of rectangle.  in [0, 2147483647]

PLUGINS: 2dtransform/io

       bbs       Binary (non-portable) serialized IO of 2D transformations

                     Recognized file extensions:  .bbs

       datapool  Virtual IO to and from the internal data pool

                     Recognized file extensions:  .@

       vista     Vista storage of 2D transformations

                     Recognized file extensions:  .v2dt

       xml       XML serialized IO of 2D transformations

                     Recognized file extensions:  .x2dt

PLUGINS: generator/noise

       gauss     This  noise  generator creates random values that are distributed according to a
                 Gaussien  distribution  by  using  the  Box-Muller  transformation.,   supported
                 parameters are:

                     mu = 0 (float)
                       mean of distribution.  in [-3.40282e+38, 3.40282e+38]

                     seed = 0 (uint)
                       set random seed (0=init based on system time).  in [0, 4294967295]

                     sigma = 1 (float)
                       standard derivation of distribution.  in [0, 3.40282e+38]

       uniform   Uniform noise generator using C stdlib rand(), supported parameters are:

                     a = 0 (float)
                       lower bound if noise range.  in [-3.40282e+38, 3.40282e+38]

                     b = 1 (float)
                       higher bound if noise range.  in [-3.40282e+38, 3.40282e+38]

                     seed = 0 (uint)
                       set random seed (0=init based on system time).  in [0, 4294967295]

EXAMPLE

       Evaluate  the  median  of the 2nd order derivative of the series given in segmentation set
       segment.set after filtering with a Gaussian  of  width  3.  In  addition  write  the  time
       intensity curve of pixel <128,64> to curve.txt.

       mia-2dseries2dordermedian  -i  segment.set  -o  gradmedian.exr  -g  1 --itc-file curve.txt
              --itc-loc "<128,64>"

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'.