mia-2dmyomilles

Sysnopis:

mia-2dmyomilles {-i string} {-o string} [ options ...]

Description:

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.

Options:

File-IO

-i, --in-file=(input, required); string

input perfusion data set

-o, --out-file=(output, required); string

output perfusion data set

-r, --registered=STRING

file name base for registered files

--save-references=STRING

save synthetic reference images to this file base

--save-cropped=STRING

save cropped image set to this file

--save-feature=STRING

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; dict

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=(); bool

print copyright information

-h, --help=(); bool

print this help

-?, --usage=(); bool

print a short help

--version=(); bool

print the version number and exit

ICA

-C, --components=0; ulong

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; float

segment and scale the crop box around the LV (0=no segmentation)

-k, --skip=0; ulong

skip images at the beginning of the series as they are of other modalities

-m, --max-ica-iter=400; ulong

maximum number of iterations in ICA

-E, --segmethod=features; dict

Segmentation method

delta-peak:difference of the peak enhancement images
features:feature images
delta-feature:difference of the feature images

Processing

--threads=-1; int

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; stringSTRING

registration criterion

-O, --optimizer=gsl:opt=simplex,step=1.0; factory

Optimizer used for minimization. For supported plug-ins see Plugin type: minimizer/singlecost

-f, --transForm=rigid; factory

transformation type. For supported plug-ins see Plugin type: 2dimage/transform

-l, --mg-levels=3; ulong

multi-resolution levels

-R, --reference=-1; int

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; ulong

registration passes

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