mia-2dmany2one-nonrigid(1)

✨ NAME ✨

mia-2dmany2one-nonrigid — Registration of a series of 2D images 🦋

okay so bestie, this is the manual page for mia-2dmany2one-nonrigid, and she is that girl. let's get into it 💅

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🌈 SYNOPSIS 🌈

mia-2dmany2one-nonrigid -i <in-file> -o <out-file> [options]
<PLUGINS:2dimage/fullcost>

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💖 DESCRIPTION 💖

mia-2dmany2one-nonrigid — this program registers all images of a consecutively numbered set of images to one common, user-defined reference. no cap, every single one of them, all matching up to the same reference frame you picked. periodt ✨

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🎀 OPTIONS 🎀

📁 File-IO

• -i, --in-file=(input, required); string — the input perfusion data set, bestie. you gotta give her this one, she's required 🥺
• -o, --out-file=(output, required); string — file name for the registered images. the numbering and the pattern get deducted from the input data, so she figures that out herself. also required, don't ghost her 💀

🌀 Registration

• -O, --optimizer=gsl:opt=gd,step=0.1 — the optimizer used for minimization. defaults to that exact string up there, character for character 👑
• -l, --mg-levels=3 — multi-resolution levels. three of them, by default 🪜
• -f, --transForm=spline — transformation type. for supported plugins see PLUGINS:2dimage/transform 🦋
• -r, --ref=-1 — reference frame. and -1 == use image in the middle, which is honestly such a main character move 🌟
• -k, --skip=0 — skip registration of these images at the beginning of the series. zero by default, so nothing gets skipped unless you say so 🙈

🫶 Help & Info

• -V, --verbose=warning — verbosity of output; it prints messages of the given level and higher priorities. the supported priorities, starting at the lowest level, are:
  • trace — Function call trace
  • debug — Debug output
  • info — Low level messages
  • message — Normal messages
  • warning — Warnings
  • fail — Report test failures
  • error — Report errors
  • 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. she leaves immediately, iconic 💅

⚙️ 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). so -1 means she counts the cores herself and handles it 🔥

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🌸 PLUGINS: 1d/splinebc 🌸

spline interpolation boundary conditions, three flavors, all of them parameter-free girlies:

mirror

Spline interpolation boundary conditions that mirror on the boundary.

(no parameters) 🪞

repeat

Spline interpolation boundary conditions that repeats the value at the boundary.

(no parameters) 🔁

zero

Spline interpolation boundary conditions that assumes zero for values outside.

(no parameters) 0️⃣

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🧚 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. yes the range is literally just [3, 3], she is very particular about it 💀

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🔥 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. 🪟

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. ✂️
• mbins = 64; uint in [1, 256]
  • 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
• rbins = 64; uint in [1, 256]
  • 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

ncc

normalized cross correlation.

(no parameters) 🎯

ngf

This function evaluates the image similarity based on normalized gradient fields. Various evaluation kernels are available., 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

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. 🚧
• norm = 0; bool
  • 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.
• sthresh = 0; double
  • Threshold intensity value for source image.

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💜 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
• debug = 0; bool
  • Save intermediate resuts for debugging. 🐛
• ref =(input, io)
  • Reference image. For supported file types see PLUGINS:2dimage/io
• src =(input, io)
  • Study image. For supported file types see PLUGINS:2dimage/io
• weight = 1; float
  • 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.
• maxlabel = 256; int in [2, 32000]
  • maximum number of labels to consider. 🏷️
• ref =(input, io)
  • Reference image. For supported file types see PLUGINS:2dimage/io
• src =(input, io)
  • Study image. For supported file types see PLUGINS:2dimage/io
• weight = 1; float
  • 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
• ref =(input, io)
  • Reference image. For supported file types see PLUGINS:2dimage/io
• ref-mask =(input, io)
  • Reference image mask (binary). For supported file types see PLUGINS:2dimage/io
• src =(input, io)
  • Study image. For supported file types see PLUGINS:2dimage/io
• src-mask =(input, io)
  • Study image mask (binary). For supported file types see PLUGINS:2dimage/io
• weight = 1; float
  • weight of cost function.

🫶 heads up bestie, the mask one is highkey strict about those masks being densly filled regions in multi-resolution procesing — otherwise the mask info can get lost when the image is downscaled. binary AND combines the reference mask with the transformed mask of the study image, and that's the whole vibe.

🌈 PLUGINS: 2dimage/io 🌈

okay bestie, these are the plugins that read and write your 2D images, and honestly the range here is giving "we contain multitudes" 💅

• bmp — BMP 2D-image input/output support. This plug-in can read and write binary images plus 8-bit gray scale images. For 4-bit gray scale images it's read-only, so no writing those, sorry. The color table gets straight-up ignored and the pixel values are taken as literal gray scale values. iconic behaviour, honestly.

Recognized file extensions: .BMP, .bmp

Supported element types:

• binary data, unsigned 8 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

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✨ PLUGINS: 2dimage/maskedcost ✨

these are the cost functions that also respect a mask, so you can tell the registration which pixels to actually care about 🫶

• 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.
• 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.
  • mbins = 64; uint in [1, 256] — 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
  • rbins = 64; uint in [1, 256] — 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
• ncc — normalized cross correlation with masking support.

(no parameters)

• ssd — Sum of squared differences with masking.

(no parameters)

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🦋 PLUGINS: 2dimage/transform 🦋

these are the actual transformations, i.e. how your image gets moved around, and there are so many flavours bestie 🧚

• affine — Affine transformation (six degrees of freedom)., supported parameters are:
  • imgboundary = mirror; factory — image interpolation boundary conditions. For supported plug-ins see PLUGINS:1d/splinebc
  • imgkernel = [bspline:d=3]; factory — image interpolator kernel. For supported plug-ins see PLUGINS:1d/splinekernel
• rigid — Rigid transformations (i.e. rotation and translation, three degrees of freedom)., supported parameters are:
  • imgboundary = mirror; factory — image interpolation boundary conditions. For supported plug-ins see PLUGINS:1d/splinebc
  • imgkernel = [bspline:d=3]; factory — image interpolator kernel. For supported plug-ins see PLUGINS:1d/splinekernel
  • rot-center = [[0,0]]; 2dfvector — Relative rotation center, i.e. <0.5,0.5> corresponds to the center of the support rectangle.
• rotation — Rotation transformations (i.e. rotation about a given center, one degree of freedom)., supported parameters are:
  • imgboundary = mirror; factory — image interpolation boundary conditions. For supported plug-ins see PLUGINS:1d/splinebc
  • imgkernel = [bspline:d=3]; factory — image interpolator kernel. For supported plug-ins see PLUGINS:1d/splinekernel
  • rot-center = [[0,0]]; 2dfvector — Relative rotation center, i.e. <0.5,0.5> corresponds to the center of the support rectangle.
• spline — Free-form transformation that can be described by a set of B-spline coefficients and an underlying B-spline kernel., supported parameters are:
  • anisorate = [[0,0]]; 2dfvector — anisotropic coefficient rate in pixels, nonpositive values will be overwritten by the rate value..
  • imgboundary = mirror; factory — image interpolation boundary conditions. For supported plug-ins see PLUGINS:1d/splinebc
  • imgkernel = [bspline:d=3]; factory — image interpolator kernel. For supported plug-ins see PLUGINS:1d/splinekernel
  • kernel = [bspline:d=3]; factory — transformation spline kernel.. For supported plug-ins see PLUGINS:1d/splinekernel
  • penalty = ; factory — Transformation penalty term. For supported plug-ins see PLUGINS:2dtransform/splinepenalty
  • rate = 10; float in [1, inf) — isotropic coefficient rate in pixels.
• translate — Translation only (two degrees of freedom), supported parameters are:
  • imgboundary = mirror; factory — image interpolation boundary conditions. For supported plug-ins see PLUGINS:1d/splinebc
  • imgkernel = [bspline:d=3]; factory — image interpolator kernel. For supported plug-ins see PLUGINS:1d/splinekernel
• vf — This plug-in implements a transformation that defines a translation for each point of the grid defining the domain of the transformation., supported parameters are:
  • imgboundary = mirror; factory — image interpolation boundary conditions. For supported plug-ins see PLUGINS:1d/splinebc
  • imgkernel = [bspline:d=3]; factory — image interpolator kernel. For supported plug-ins see PLUGINS:1d/splinekernel

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💜 PLUGINS: 2dtransform/splinepenalty 💜

• divcurl — divcurl penalty on the transformation, supported parameters are:
  • curl = 1; float in [0, inf) — penalty weight on curl.
  • div = 1; float in [0, inf) — penalty weight on divergence.
  • norm = 0; bool — Set to 1 if the penalty should be normalized with respect to the image size.
  • weight = 1; float in (0, inf) — weight of penalty energy.

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🌸 EXAMPLE 🌸

Register the image series given by images inputXXXX.png to reference image 30. Skip two images at the beginning and using mutual information as cost function, and penalize the transformation by divcurl with weight 5. Store the result in registeredXXXX.png.

mia-2dmany2one-nonrigid   -i input0000.png -o registered%04d.png -k 2 -r
       30 image:cost=mi divcurl:weight=5

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👑 AUTHOR(s) 👑

Gert Wollny

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📜 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.

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okay that's the whole page bestie, you ate 💅✨ This was the user commands section of the mia-2dmany2one-nonrigid page, version v2.4.7, dated mia-2dmany2one-nonrigid(1). go forth and register some images, no cap 🎀🦋💖