xenial (1) mia-2dseriesgradMAD.1.gz
NAME
mia-2dseriesgradMAD - Evaluate the time-intensity gradient MAD in a series of images.
SYNOPSIS
mia-2dseriesgradMAD -i <in-file> -o <out-file> [options] <PLUGINS:2dimage/filter>
DESCRIPTION
mia-2dseriesgradMAD Given a set of images of temporal sucession, evaluates the pixel-wise temporal
gradient and then its median average distance (MAD) and stores the result in an image. Spacial pre-
filtering may be applied as given additional plugin(s) (filter/2dimage).
OPTIONS
-i --in-file=(input, required); string
input segmentation set
-o --out-file=(output, required); io
output file name For supported file types see PLUGINS:2dimage/io
-k --skip=0
Skip files at the beginningSkip files at the beginning
-e --enlarge-boundary=5
Enlarge cropbox by number of pixelsEnlarge cropbox by number of pixels
-c --crop
crop image before running statistics
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
trace ‐ Function call trace
fail ‐ Report test failures
warning ‐ Warnings
error ‐ Report errors
debug ‐ Debug output
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).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
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.
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: 2dimage/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: 2dimage/filter
adaptmed 2D image adaptive median filter, supported parameters are:
w = 2; int in [1, inf)
half filter width.
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 in [1, inf)
half filter width.
aniso 2D Anisotropic image filter, supported parameters are:
epsilon = 1; float in (0, inf)
iteration change threshold.
iter = 100; int in [1, 10000]
number of iterations.
k = -1; float in [0, 100]
k the noise threshold (<=0 -> adaptive).
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.
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; 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
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 =(input, required, string)
second image that is needed in the combiner.
op =(required, factory)
Image combiner to be applied to the images. For supported plug-ins see
PLUGINS:2dimage/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:
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:
none ‐ no pixel type defined
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 in [1, inf)
blocksize in x direction.
by = 1; uint in [1, inf)
blocksize in y direction.
kernel = gauss; string
smoothing filter kernel to be applied, the size of the filter is estimated based on the
blocksize..
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 in [0, inf)
filter width parameter.
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 in [2, inf)
number of classes.
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 Image filter to remap label id's. Only applicable to images with integer valued
intensities/labels., supported parameters are:
map =(input, required, 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, 2dbounds)
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 =(input, required, string)
name of the input file to load from..
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 =(input, required, string)
second input image file name.
inverse = 0; bool
set to true to use the inverse of the mask for masking.
maxflow This filter implements the uses the max-flow min-cut algorithmfor image segmentation, supported
parameters are:
sink-flow =(input, required, string)
Image of float type to define the per-pixel flow to the sink.
source-flow =(input, required, string)
Image of float type to define the per-pixel flow to the source.
mean 2D image mean filter, supported parameters are:
w = 1; int in [1, inf)
half filter width.
median 2D image median filter, supported parameters are:
w = 1; int in [1, inf)
half filter width.
mlv Mean of Least Variance 2D image filter, supported parameters are:
w = 1; int in [1, inf)
filter width parameter.
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 in [1, 1000000]
Number of iterations to run, 0=until convergence.
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 =(input, required, string)
seed image (bit valued).
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 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 in [0, inf)
target size in x direction, 0: use input size.
sy = 0; uint in [0, inf)
target size in y direction, 0: use input size.
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
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:
y ‐ gradient in y-direction
x ‐ gradient in x-direction
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 =(input, 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 =(output, required, string)
name of the output file to save the image too..
thinning Morphological thinning. Thinning until convergence will result in a 8-connected skeleton,
supported parameters are:
iter = 0; int in [1, 1000000]
Number of iterations to run, 0=until convergence.
thresh This filter sets all pixels of an image to zero that fall below a certain threshold and whose
neighbours in a given neighborhood shape also fall below a this threshold, supported parameters
are:
shape = 4n; factory
neighborhood shape to take into account. For supported plug-ins see
PLUGINS:2dimage/shape
thresh = 5; double
The threshold value.
transform Transform the input image with the given transformation., supported parameters are:
file =(input, required, string)
Name of the file containing the transformation..
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 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: 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:
signed 16 bit, 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 in [1, inf)
height of rectangle.
width = 2; int in [1, inf)
width of rectangle.
sphere Closed spherical neighborhood shape of radius r., supported parameters are:
r = 2; float in (0, inf)
sphere radius.
square square shape mask creator, supported parameters are:
fill = 1; bool
create a filled shape.
width = 2; int in [1, inf)
width of rectangle.
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.
seed = 0; uint in [0, inf)
set random seed (0=init based on system time).
sigma = 1; float in (0, inf)
standard derivation of distribution.
uniform Uniform noise generator using C stdlib rand(), supported parameters are:
a = 0; float
lower bound if noise range.
b = 1; float
higher bound if noise range.
seed = 0; uint in [0, inf)
set random seed (0=init based on system time).
EXAMPLE
Evaluate the MAD-image of the bounding box surrounding the segmentation from a series segment.set. 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-2dseriesgradMAD -i segment.set -o mad.exr -c -e 3
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'.