Provided by: mia-tools_2.0.13-1_amd64 
NAME
mia-2dseriessmoothgradMAD - Evaluate pixel-wise time-intensity gradient of a 2D image series.
SYNOPSIS
mia-2dseriessmoothgradMAD -i <in-file> -o <out-file> [options] <PLUGINS:2dimage/filter>
DESCRIPTION
mia-2dseriessmoothgradMAD Given a set of images of temporal sucession, evaluate the temporal pixel-wise
gaussian and evaluate pixel-wise its MAD.A spacial pre-filtering may be applied by specifying additional
plugins (filter/2dimage)
OPTIONS
-i --in-file=(required)
input segmentation set
-o --out-file=(required)
output file 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
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 MAD-image of the bounding box surrounding the segmentation from a series segment.set after
applying a temporal Gaussian filter of width 5. No spacial filtering will be applied. The bounding box
will be enlarged by 3 pixels in all directions. Store the image in OpenEXR format.
mia-2dseriessmoothgradMAD -i segment.set -o mad.exr -g 2 -c -e 3
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'.