--- name: "mia-2dmyomilles" section: "1" platform: "linux" package: "mia-tools" version: "2.4.7-11+b1" release: "Debian 12 (Bookworm)" platforms: ["linux"] url: "https://new.carta.tech/mia-2dmyomilles" --- # mia-2dmyomilles(1) Run a registration of a series of 2D images. ## NAME mia-2dmyomilles - Run a registration of a series of 2D images. ## SYNOPSIS **mia-2dmyomilles -i \ -o \ \[options\]** ## DESCRIPTION **mia-2dmyomilles** This program is use to run a modified version of the ICA based registration approach described in Milles et al. 'Fully Automated Motion Correction in First-Pass Myocardial Perfusion MR Image Sequences', Trans. Med. Imaging., 27(11), 1611-1621, 2008. ⟨https://doi.org/10.1109/TMI.2008.928918⟩ Changes include the extraction of the quasi-periodic movement in free breathingly acquired data sets and the option to run affine or rigid registration instead of the optimization of translations only. ## OPTIONS ### File-IO - \-i --in-file=(required, input); string input perfusion data set - \-o --out-file=(required, output); string output perfusion data set - \-r --registered= file name base for registered files - \--save-references= save synthetic reference images to this file base - \--save-cropped= save cropped image set to this file - \--save-feature= save the features images resulting from the ICA and some intermediate images used for the RV-LV segmentation with the given file name base to PNG files. Also save the coefficients of the initial best and the final IC mixing matrix. ### Help & Info - \-V --verbose=warning verbosity of output, print messages of given level and higher priorities. Supported priorities starting at 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 ### ICA - \--fastica=internal FastICA implementationto be used\ For supported plugins see PLUGINS:fastica/implementation - \-C --components=0 ICA components 0 = automatic estimation - \--normalize normalized ICs - \--no-meanstrip don't strip the mean from the mixing curves - \-g --guess use initial guess for myocardial perfusion - \-s --segscale=1.4 segment and scale the crop box around the LV (0=no segmentation) - \-k --skip=0 skip images at the beginning of the series as they are of other modalities - \-m --max-ica-iter=400 maximum number of iterations in ICA - \-E --segmethod=features Segmentation method *delta-feature* ‐ difference of the feature images *delta-peak* ‐ difference of the peak enhancement images *features* ‐ feature images ### 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). ### Registration - \-c --cost=ssd registration criterion - \-O --optimizer=gsl:opt=simplex,step=1.0 Optimizer used for minimization\ For supported plugins see PLUGINS:minimizer/singlecost - \-f --transForm=rigid transformation type\ For supported plugins see PLUGINS:2dimage/transform - \-l --mg-levels=3 multi-resolution levels - \-R --reference=-1 Global reference all image should be aligned to. If set to a non-negative value, the images will be aligned to this references, and the cropped output image date will be injected into the original images. Leave at -1 if you don't care. In this case all images with be registered to a mean position of the movement - \-P --passes=2 registration passes ## PLUGINS: 1d/splinebc - **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) ## 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/transform - **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 ## 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. ## PLUGINS: fastica/implementation - **internal** This is the MIA implementation of the FastICA algorithm. (no parameters) - **itpp** This is the IT++ implementation of the FastICA algorithm. (no parameters) ## PLUGINS: minimizer/singlecost - **gdas** Gradient descent with automatic step size correction., supported parameters are: *ftolr* = 0; double in \[0, inf) Stop if the relative change of the criterion is below.. *max-step* = 2; double in (0, inf) Maximal absolute step size. *maxiter* = 200; uint in \[1, inf) Stopping criterion: the maximum number of iterations. *min-step* = 0.1; double in (0, inf) Minimal absolute step size. *xtola* = 0.01; double in \[0, inf) Stop if the inf-norm of the change applied to x is below this value.. - **gdsq** Gradient descent with quadratic step estimation, supported parameters are: *ftolr* = 0; double in \[0, inf) Stop if the relative change of the criterion is below.. *gtola* = 0; double in \[0, inf) Stop if the inf-norm of the gradient is below this value.. *maxiter* = 100; uint in \[1, inf) Stopping criterion: the maximum 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 if the inf-norm of x-update is below this value.. - **gsl** optimizer plugin based on the multimin optimizers of the GNU Scientific Library (GSL) https://www.gnu.org/software/gsl/, supported parameters are: *eps* = 0.01; double in (0, inf) gradient based optimizers: stop when \|grad\| \< eps, simplex: stop when simplex size \< eps.. *iter* = 100; uint in \[1, inf) maximum number of iterations. *opt* = gd; dict Specific optimizer to be used.. 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 please see 'http://ab-initio.mit.edu/wiki/index.php/NLopt\_Algorithms', supported parameters are: *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 automatic ICA estimation. Skip two images at the beginning and otherwiese use the default parameters. Store the result in 'registered.set'. mia-2dmyomilles -i segment.set -o registered.set -k 2 ## 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'.