Talairach Transformation From Normalization

Compute the subject T1 MRI to Talairach-AC/PC transformation, using a normalization matrix.

Description

Compute the subject T1 MRI to Talairach-AC/PC transformation, using a normalization matrix. The classical T1 pipeline in BrainVISA generates it only from a manual determination of AC and PC positions (see Prepare Subject), and from the brain bounding box, which is far from perfect in the cortex (see the Talairach Transformation process).

Using this alternative, normalization information may replace the manual AC/PC procedure, and should be more accurate. Normalization matrices, as their name states it, are affine transformations: elastic deformation information cannot be used. But an affine part in a non-linear normalization might be OK, like the affine part of SPM normalization.

SPM *_sn.mat normalization matrices may be converted using the SPM normalization to AIMS converter process, then given as input to this one.

The input normalization matrix is going from the subject space (its T1 image) to a common referential. The common referential should be known within BrainVISA so that BrainVISA knows how to go from this common referential to the Talairach AC/PC space. It will generally be the MNI template referential, but could be any referential with a known transformation to Talairach-AC/PC.


Optionally, AC/PC information may be retreived from the normalized space, and the commissure coordinates file (normally written by the Prepare Subject process) may be written (or replaced) with the new information.


If this process is run after a full T1 pipeline has already run, some information within the cortical folds graphs should be updated and recalculates. So users should run the Cortical Folds Graph Upgrade process. Morphometric measurements may change also since they are not measured in the same space anymore.

Parameters

normalization_transformation: Transform Raw T1 MRI to Talairach-MNI template-SPM ( input )
Input normalization matrix (subject T1 to a common space, the MNI template typically)
Talairach_transform: Transform Raw T1 MRI to Talairach-AC/PC-Anatomist ( output )
Output transformation, going from the subject T1 space to the Talairach-AC/PC space
commissure_coordinates: Commissure coordinates ( optional, output )
t1mri: Raw T1 MRI ( optional, input )
Raw T1 MRI, needed only if writing the commissure coordinates file.
source_referential: Referential ( input )
Normally, the referential of the subject T1 MRI image
normalized_referential: Referential ( input )
This is the destination referential of the input normalization matrix
transform_chain_ACPC_to_Normalized: ListOf( Transformation ) ( input )
acpc_referential: Referential ( optional, input )

Technical information

Toolbox : Morphologist

User level : 2

Identifier : TalairachTransformationFromNormalization

File name : brainvisa/toolboxes/morphologist/processes/segmentationpipeline/components/TalairachTransformationFromNormalization.py

Supported file formats :

normalization_transformation :
Transformation matrix, Transformation matrix
Talairach_transform :
Transformation matrix, Transformation matrix
commissure_coordinates :
Commissure coordinates, Commissure coordinates
t1mri :
gz compressed NIFTI-1 image, Aperio svs, BMP image, DICOM image, Directory, ECAT i image, ECAT v image, FDF image, FreesurferMGH, FreesurferMGZ, GIF image, GIS image, Hamamatsu ndpi, Hamamatsu vms, Hamamatsu vmu, JPEG image, Leica scn, MINC image, NIFTI-1 image, PBM image, PGM image, PNG image, PPM image, SPM image, Sakura svslide, TIFF image, TIFF image, TIFF(.tif) image, TIFF(.tif) image, VIDA image, Ventana bif, XBM image, XPM image, Zeiss czi, gz compressed MINC image, gz compressed NIFTI-1 image
source_referential :
Referential, Referential
normalized_referential :
Referential, Referential
transform_chain_ACPC_to_Normalized :
Transformation matrix, Transformation matrix
acpc_referential :
Referential, Referential