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=(input, required); string

input segmentation set

-o --out-file=(output, required); io

output image 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

-g --gauss=1

gauss filter width for moothing the gradientgauss filter width for moothing the gradient

--itc-file=

intensity time curve output file

--itc-loc=[0,0]

intensity time curve output pixel coordinatesintensity 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

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 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) 1999-2015 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'.