Rigid registration with mutual information

Interface AimsMIRegister

Description

This process interfaces registration command AimsMIRegister and proposes to compute (or not) new resampled image.

Method of registration is based on an iconic approach, based on voxels grey levels. It uses mutual information (statistical dependence between 2 variables) to compute the registration.

A rigid transformation is calculated between the reference image and source image (translation and matrix rotation) with similar field of view.

If images are 4D Volume, then an automatic sum of all the frames is made to obtain a 3D Volume.

Matrix transformation:

The format file of matrix transformation is .trm and its syntax is:

*TO*.trm (* indicates all types of characters or character string).





Format files

Initialization of registration:

There are 2 modes for initialization of registration:

Sub-resolution of reference image:

Reference image can be damaged with a reduction factor according to the principle of a pyramid.

value 1 --> 1 voxel out of 2 in the 3 directions --> reduction by a factor of 8

value 1 --> 1 voxel out of 4 in the 3 directions --> reduction by a factor of 64





Registration of source image:

The AimsMIRegister command allows the determination of a matrix transformation file. You can choose to apply this matrix transformation to the source image. Then you must indicate the name of the registred image for resampled_image. You can then choose the method of interpolation with resampled_interpolation.



Example:
Here is a registration of a source image (fonc.ima) with a reference image (anat.ima). The output files are refTOtest.trm, testTOref.trm and resampfonc.ima (registred image). Ouput files for this process are not currently managed by database. Thus you must use icon to indicate output files.



Process BrainVISA: Rigid registration with mutual information

Parameters

source_image: 4D Volume ( input )
reference_image: 4D Volume ( input )
source_to_reference: Transformation matrix ( output )
reference_to_source: Transformation matrix ( output )
init_with_gravity_center: Boolean ( input )
reference_threshold: Float ( input )
source_threshold: Float ( input )
reference_reduction_factor: Integer ( input )
initial_translation_x: Float ( optional, input )
initial_translation_y: Float ( optional, input )
initial_translation_z: Float ( optional, input )
initial_rotation_x: Float ( optional, input )
initial_rotation_y: Float ( optional, input )
initial_rotation_z: Float ( optional, input )
step_translation_x: Float ( optional, input )
step_translation_y: Float ( optional, input )
step_translation_z: Float ( optional, input )
step_rotation_x: Float ( optional, input )
step_rotation_y: Float ( optional, input )
step_rotation_z: Float ( optional, input )
error_epsilon: Float ( input )
resampled_image: 4D Volume ( optional, output )
resampled_interpolation: Choice ( input )

Technical information

Toolbox : Tools

User level : 0

Identifier : Register3DMutualInformation

File name : brainvisa/toolboxes/tools/processes/registration/Register3DMutualInformation.py

Supported file formats :

source_image :
GIS image, VIDA image, NIFTI-1 image, MINC image, gz compressed MINC image, DICOM image, TIFF image, XBM image, PBM image, PGM image, BMP image, XPM image, PPM image, gz compressed NIFTI-1 image, TIFF(.tif) image, ECAT i image, PNG image, JPEG image, MNG image, GIF image, SPM image, ECAT v image
reference_image :
GIS image, VIDA image, NIFTI-1 image, MINC image, gz compressed MINC image, DICOM image, TIFF image, XBM image, PBM image, PGM image, BMP image, XPM image, PPM image, gz compressed NIFTI-1 image, TIFF(.tif) image, ECAT i image, PNG image, JPEG image, MNG image, GIF image, SPM image, ECAT v image
source_to_reference :
Transformation matrix
reference_to_source :
Transformation matrix
resampled_image :
GIS image, VIDA image, NIFTI-1 image, MINC image, TIFF image, XBM image, PBM image, PGM image, BMP image, XPM image, PPM image, gz compressed NIFTI-1 image, ECAT i image, PNG image, JPEG image, MNG image, GIF image, SPM image, ECAT v image