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. 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.
input perfusion data set
output perfusion data set
file name base for registered files
save synthetic reference images to this file base
save cropped image set to this file
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.
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|
|fatal:||Report only fatal errors|
print copyright information
print this help
print a short help
print the version number and exit
ICA components 0 = automatic estimation
don't strip the mean from the mixing curves
use initial guess for myocardial perfusion
segment and scale the crop box around the LV (0=no segmentation)
skip images at the beginning of the series as they are of other modalities
maximum number of iterations in ICA
|delta-peak:||difference of the peak enhancement images|
|delta-feature:||difference of the feature images|
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).
Optimizer used for minimization. For supported plug-ins see Plugin type: minimizer/singlecost
transformation type. For supported plug-ins see Plugin type: 2dimage/transform
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
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