mia-2dmyopgt-nonrigid(1)

📦
version 2.4.7 · 3 versions
, in debian bookworm, ubuntu jammy

💖 mia-2dmyopgt-nonrigid(1) 💖

okay bestie, sit down, hydrate, because this is the mia-2dmyopgt-nonrigid manual page and it is lowkey a whole journey 🫶 it lives in the General Commands Manual section, and it is about to make your 2D image series look ✨registered✨

🌸 NAME 🌸

mia-2dmyopgt-nonrigid — Run a registration of a series of 2D images. no cap, that's literally the whole job 💅

✨ SYNOPSIS ✨

mia-2dmyopgt-nonrigid -i <in-file> -o <out-file> [options]

like. give it an input, give it an output, sprinkle options on top. that's the vibe 🎀

🦋 DESCRIPTION 🦋

mia-2dmyopgt-nonrigid implements the non-linear registration based on Pseudo Ground Thruth for motion compensation of series of myocardial perfusion images, and it wants those images handed to it as a data set, exactly as described in:

Chao Li and Ying Sun, 'Nonrigid Registration of Myocardial Perfusion MRI Using Pseudo Ground Truth' , In Proc. Medical Image Computing and Computer-Assisted Intervention MICCAI 2009, 165-172, 2009

so yeah, this is a Real Academic Situation and the program is the main character 📚👑

💅 OPTIONS 💅

🎀 File-IO 🎀

the boring-but-essential part. in goes data, out comes data. iconic behaviour honestly.

  • -i, --in-file=(input, required); string — input perfusion data set. this one is required, bestie, no input no party 🙈
  • -o, --out-file=(output, required); string — output perfusion data set. also required, we do not do silent nothingness here 💀
  • -r, --registered=reg — file name base for registered files, and the image file type is the same as given in the input data set. so it inherits the format from your input, slay 🌈

🔮 Pseudo Ground Thruth estimation 🔮

this is where the actual science happens. the "Thruth" is spelled like that in the original, and honestly? she's earned it 👑

  • -A, --alpha=1 — spacial neighborhood penalty weight (default 1) 🍓
  • -B, --beta=1 — temporal second derivative penalty weight (default 1) ⏳
  • -R, --rho-thresh=0.85 — correlation threshold for neighborhood analysis (default 0.85) 📈
  • -k, --skip=0 — skip images at the beginning of the series, e.g. because as they are of other modalities (default 0). so like, the first few frames are a different vibe entirely and you just walk past them 💅

🧚 Registration 🧚

the minimisation era of your life. buckle up.

  • -O, --optimizer=gsl:opt=gd,step=0.1 — Optimizer used for minimization (default gsl:opt=gd,step=0.1). For supported plugins see PLUGINS:minimizer/singlecost 🔌
  • -a, --start-c-rate=32 — start coefficinet rate in spines, gets divided by --c-rate-divider with every pass (default 32) 🌀
  • --c-rate-divider=4 — cofficient rate divider for each pass (default 4) ➗
  • -d, --start-divcurl=20 — start divcurl weight, gets divided by --divcurl-divider with every pass (default 20) 🌊
  • --divcurl-divider=4 — divcurl weight scaling with each new pass (default 4) 🪄
  • -w, --imageweight=1 — image cost weight (default 1) ⚖️
  • -l, --mg-levels=3 — multi-resolution levels (default 3) 🪜
  • -P, --passes=4 — registration passes (default 4) 🔁

💖 Help & Info 💖

your little support system. they don't do the math, they just tell you things.

  • -V, --verbose=warning — verbosity of output, print messages of given level and higher priorities (default warning). Supported priorities starting at lowest level are:
    1. trace ‐ Function call trace
    2. debug ‐ Debug output
    3. info ‐ Low level messages
    4. message ‐ Normal messages
    5. warning ‐ Warnings
    6. fail ‐ Report test failures
    7. error ‐ Report errors
    8. 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 🌈

the "how much of my CPU am I willing to sacrifice" section.

  • --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 like, -1 means "bestie just figure it out yourself" and it does 💀🔥

still with me? good. there's more coming — this page is a two-parter, so don't go anywhere 🌸

🔌 PLUGINS: minimizer/singlecost 💅

okay so these are the minimizer plugins you can drop into singlecost — pick your fighter, bestie, each one has its own little knobs ✨

  • gdas — Gradient descent with automatic step size correction. The parameters it supports are:
    • ftolr = 0; double in [0, inf) — stop when the relative change of the criterion dips below this.
    • max-step = 2; double in (0, inf) — the biggest absolute step size allowed.
    • maxiter = 200; uint in [1, inf) — stopping criterion: max number of iterations.
    • min-step = 0.1; double in (0, inf) — the smallest absolute step size allowed.
    • xtola = 0.01; double in [0, inf) — stop when the inf-norm of the change applied to x is below this value.
  • gdsq — Gradient descent with quadratic step estimation. Parameters:
    • ftolr = 0; double in [0, inf) — stop when the relative change of the criterion is below this.
    • gtola = 0; double in [0, inf) — stop when the inf-norm of the gradient is below this value.
    • maxiter = 100; uint in [1, inf) — stopping criterion: max number of iterations.
    • scale = 2; double in (1, inf) — fallback fixed step size scaling.
    • step = 0.1; double in (0, inf) — initial step size.
    • xtola = 0; double in [0, inf) — stop when the inf-norm of the x-update is below this value.
  • gsl — optimizer plugin built on the multimin optimizers from the GNU Scientific Library (GSL), https://www.gnu.org/software/gsl/. Parameters:
    • eps = 0.01; double in (0, inf) — for gradient based optimizers: stop when |grad| < eps; for simplex: stop when simplex size < eps.
    • iter = 100; uint in [1, inf) — maximum number of iterations.
    • opt = gd; dict — the specific optimizer to use. Supported values are:
      • simplex ‐ Simplex algorithm of Nelder and Mead
      • cg-fr ‐ Flecher-Reeves conjugate gradient algorithm
      • cg-pr ‐ Polak-Ribiere conjugate gradient algorithm
      • bfgs ‐ Broyden-Fletcher-Goldfarb-Shann
      • bfgs2 ‐ Broyden-Fletcher-Goldfarb-Shann (most efficient version)
      • gd ‐ Gradient descent.
    • step = 0.001; double in (0, inf) — initial step size.
    • tol = 0.1; double in (0, inf) — some tolerance parameter.
  • nlopt — minimizer algorithms using the NLOPT library. For a description of the optimizers, peep 'http://ab-initio.mit.edu/wiki/index.php/NLopt_Algorithms'. Parameters:
    • ftola = 0; double in [0, inf) — stopping criterion: the absolute change of the objective value is below this value.
    • ftolr = 0; double in [0, inf) — stopping criterion: the relative change of the objective value is below this value.
    • higher = inf; double — higher boundary (equal for all parameters).
    • local-opt = none; dict — local minimization algorithm that may be required for the main minimization algorithm. Supported values are:
      • gn-direct ‐ Dividing Rectangles
      • gn-direct-l ‐ Dividing Rectangles (locally biased)
      • gn-direct-l-rand ‐ Dividing Rectangles (locally biased, randomized)
      • gn-direct-noscal ‐ Dividing Rectangles (unscaled)
      • gn-direct-l-noscal ‐ Dividing Rectangles (unscaled, locally biased)
      • gn-direct-l-rand-noscale ‐ Dividing Rectangles (unscaled, locally biased, randomized)
      • gn-orig-direct ‐ Dividing Rectangles (original implementation)
      • gn-orig-direct-l ‐ Dividing Rectangles (original implementation, locally biased)
      • ld-lbfgs-nocedal ‐ None
      • ld-lbfgs ‐ Low-storage BFGS
      • ln-praxis ‐ Gradient-free Local Optimization via the Principal-Axis Method
      • ld-var1 ‐ Shifted Limited-Memory Variable-Metric, Rank 1
      • ld-var2 ‐ Shifted Limited-Memory Variable-Metric, Rank 2
      • ld-tnewton ‐ Truncated Newton
      • ld-tnewton-restart ‐ Truncated Newton with steepest-descent restarting
      • ld-tnewton-precond ‐ Preconditioned Truncated Newton
      • ld-tnewton-precond-restart ‐ Preconditioned Truncated Newton with steepest-descent restarting
      • gn-crs2-lm ‐ Controlled Random Search with Local Mutation
      • ld-mma ‐ Method of Moving Asymptotes
      • ln-cobyla ‐ Constrained Optimization BY Linear Approximation
      • ln-newuoa ‐ Derivative-free Unconstrained Optimization by Iteratively Constructed Quadratic Approximation
      • ln-newuoa-bound ‐ Derivative-free Bound-constrained Optimization by Iteratively Constructed Quadratic Approximation
      • ln-neldermead ‐ Nelder-Mead simplex algorithm
      • ln-sbplx ‐ Subplex variant of Nelder-Mead
      • ln-bobyqa ‐ Derivative-free Bound-constrained Optimization
      • gn-isres ‐ Improved Stochastic Ranking Evolution Strategy
      • none ‐ don't specify algorithm
    • lower = -inf; double — lower boundary (equal for all parameters).
    • maxiter = 100; int in [1, inf) — stopping criterion: the maximum number of iterations.
    • opt = ld-lbfgs; dict — main minimization algorithm. Supported values are:
      • gn-direct ‐ Dividing Rectangles
      • gn-direct-l ‐ Dividing Rectangles (locally biased)
      • gn-direct-l-rand ‐ Dividing Rectangles (locally biased, randomized)
      • gn-direct-noscal ‐ Dividing Rectangles (unscaled)
      • gn-direct-l-noscal ‐ Dividing Rectangles (unscaled, locally biased)
      • gn-direct-l-rand-noscale ‐ Dividing Rectangles (unscaled, locally biased, randomized)
      • gn-orig-direct ‐ Dividing Rectangles (original implementation)
      • gn-orig-direct-l ‐ Dividing Rectangles (original implementation, locally biased)
      • ld-lbfgs-nocedal ‐ None
      • ld-lbfgs ‐ Low-storage BFGS
      • ln-praxis ‐ Gradient-free Local Optimization via the Principal-Axis Method
      • ld-var1 ‐ Shifted Limited-Memory Variable-Metric, Rank 1
      • ld-var2 ‐ Shifted Limited-Memory Variable-Metric, Rank 2
      • ld-tnewton ‐ Truncated Newton
      • ld-tnewton-restart ‐ Truncated Newton with steepest-descent restarting
      • ld-tnewton-precond ‐ Preconditioned Truncated Newton
      • ld-tnewton-precond-restart ‐ Preconditioned Truncated Newton with steepest-descent restarting
      • gn-crs2-lm ‐ Controlled Random Search with Local Mutation
      • ld-mma ‐ Method of Moving Asymptotes
      • ln-cobyla ‐ Constrained Optimization BY Linear Approximation
      • ln-newuoa ‐ Derivative-free Unconstrained Optimization by Iteratively Constructed Quadratic Approximation
      • ln-newuoa-bound ‐ Derivative-free Bound-constrained Optimization by Iteratively Constructed Quadratic Approximation
      • ln-neldermead ‐ Nelder-Mead simplex algorithm
      • ln-sbplx ‐ Subplex variant of Nelder-Mead
      • ln-bobyqa ‐ Derivative-free Bound-constrained Optimization
      • gn-isres ‐ Improved Stochastic Ranking Evolution Strategy
      • auglag ‐ Augmented Lagrangian algorithm
      • auglag-eq ‐ Augmented Lagrangian algorithm with equality constraints only
      • g-mlsl ‐ Multi-Level Single-Linkage (require local optimization and bounds)
      • g-mlsl-lds ‐ Multi-Level Single-Linkage (low-discrepancy-sequence, require local gradient based optimization and bounds)
      • ld-slsqp ‐ Sequential Least-Squares Quadratic Programming
    • step = 0; double in [0, inf) — initial step size for gradient free methods.
    • stop = -inf; double — stopping criterion: function value falls below this value.
    • xtola = 0; double in [0, inf) — stopping criterion: the absolute change of all x-values is below this value.
    • xtolr = 0; double in [0, inf) — stopping criterion: the relative change of all x-values is below this value.

🎀 EXAMPLE 🎀

Register the perfusion series given in segment.set by using Pseudo Ground Truth estimation. Skip two images at the beginning and otherwiese use the default parameters. Store the result in registered.set.

mia-2dmyopgt-nonrigid -i segment.set -o registered.set -k 2

💖 AUTHOR(s) 💖

Gert Wollny

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.

and that's the whole page, bestie 💖 this was USER COMMANDS, version v2.4.7, and the date slot is just vibing as that same version energy. catch you in the terminal ✨🦋💅

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