SYNOPSIS
mia-2dmulti-force -o <out-file> [options] <PLUGINS:2dimage/fullcost>DESCRIPTION
mia-2dmulti-force This program evaluates the 2D image cost force norm image of a given cost function set. The input images must be of the same dimensions and gray scale (whatever bit-depth).OPTIONS
-
- -o --out-file=(output, required); io
- output norm image For supported file types see PLUGINS:2dimage/io
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/splinekernel
- bspline
- B-spline kernel creation , supported parameters are:
-
d
= 3; int in [0, 5]
-
Spline degree.
-
Spline degree.
- omoms
- OMoms-spline kernel creation, supported parameters are:
-
d
= 3; int in [3, 3]
-
Spline degree.
-
Spline degree.
PLUGINS: 2dimage/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.
-
half width of the window used for evaluating the localized cross correlation.
- lsd
- Least-Squares Distance measure
- (no parameters)
- 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.
-
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.
-
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
-
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.
-
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
-
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. Various evaluation kernels are availabe., supported parameters are:
-
eval
= ds; dict
-
plugin subtype.
Supported values are:
- sq - square of difference
- ds - square of scaled difference
- dot - scalar product kernel
- cross - cross product kernel
-
plugin subtype.
Supported values are:
- ssd
- 2D imaga 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.
-
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.
-
Set whether the metric should be normalized by the number of image pixels.
- ssd-automask
- 2D image cost: sum of squared differences, with automasking based on given thresholds, supported parameters are:
-
rthresh
= 0; double
-
Threshold intensity value for reference image.
-
Threshold intensity value for reference image.
-
sthresh
= 0; double
-
Threshold intensity value for source image.
-
Threshold intensity value for source image.
PLUGINS: 2dimage/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:2dimage/cost
-
Cost function kernel.
For supported plug-ins see PLUGINS:2dimage/cost
-
debug
= 0; bool
-
Save intermediate resuts for debugging.
-
Save intermediate resuts for debugging.
-
ref
=(input, string)
-
Reference image.
-
Reference image.
-
src
=(input, string)
-
Study image.
-
Study image.
-
weight
= 1; float
-
weight of cost function.
-
weight of cost function.
- labelimage
- Similarity cost function that maps labels of two images and handles label-preserving multi-resolution processing., supported parameters are:
-
debug
= 0; int in [0, 1]
-
write the distance transforms to a 3D image.
-
write the distance transforms to a 3D image.
-
maxlabel
= 256; int in [2, 32000]
-
maximum number of labels to consider.
-
maximum number of labels to consider.
-
ref
=(input, string)
-
Reference image.
-
Reference image.
-
src
=(input, string)
-
Study image.
-
Study image.
-
weight
= 1; float
-
weight of cost function.
-
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 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:2dimage/maskedcost
-
Cost function kernel.
For supported plug-ins see PLUGINS:2dimage/maskedcost
-
ref
=(input, string)
-
Reference image.
-
Reference image.
-
ref-mask
=(input, string)
-
Reference image mask (binary).
-
Reference image mask (binary).
-
src
=(input, string)
-
Study image.
-
Study image.
-
src-mask
=(input, string)
-
Study image mask (binary).
-
Study image mask (binary).
-
weight
= 1; float
-
weight of cost function.
-
weight of cost function.
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/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.
-
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.
-
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.
-
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
-
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.
-
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
-
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)
EXAMPLE
Evaluate the force normimage weighted sum of costs SSD and NGF of image1.v and image2.v. and store the result to force.v.- mia-2dmulti-force -o force.v
image:cost=ssd,src=image1.v,ref=image2.v,weight=0.1
image:cost=ngf,src=image1.v,ref=image2.v,weight=2.0
AUTHOR(s)
Gert WollnyCOPYRIGHT
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'.