Automatic Matching

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Automatic Matching

In order to use the automatic matching methods, the Auto tab must be brought to the foreground after loading the images. The following interface appears

TabAutomaticMatching

which contains a series of user interface elements:

Rigid Matching

Allows accessing different types of rigid matching methods.

Deformable Matching (SPM5)

Allows performing procedures for transforming individual brain images into a standard anatomical coordinate space. They require a suitable template image which is already in the standard space, and an elastic matching procedure for warping the images appropriately.

Option Button 1

Contains:

The Probability Maps Normalization approach: is an implementation of the Unified Segmentation procedure developed by Ashburner et al [11]. The two variants using 3 tissue probability maps (SPM8) and using 6 probability maps (SPM12) are supported. Note that the method is only applicable for the stereotactic normalization of T1-MRI brain images to appropriate template images which can be loaded  by Autodetect. These template images are available in the PMOD installation directory  Pmod4.2/resources/templates/normalization/tpm/

Diffeomorphic Deformation (ANTS): Not yet available. Will support whole body elastic matching.

Template-based normalization for brain CT: supports the normalization of human CT brain images. NOT to be used for small animals brain

The historic Brain Normalization (SPM99)

Activating either of these buttons pops up a corresponding dialog window as described below for the different methods.

Apply Current to All

Copies the transform of the current Input series to all, overwriting the prior transforms.

picture_4076

Shows the parameters of the current transform (as a result of transformation loading, automatic matching or calculation of the inverse). Only the affine component is shown, not the elastic part of the normalizations.

Save Transformation

Allows saving the final transformation obtained from initialization, automatic matching, manual adjustments as well as the result of a transformation combination.

Inverse

Allows calculating the inverse of the current transformation. Note that this applies also if the current transformation has been calculated by the combination of multiple transformation.

Save

Allows saving the inverse transformation.

Option Button 2

Allows loading a transformation which has been saved to disk after a manual or automatic matching process. The following is done with the loaded transformation:

Load Transformation: Load a transformation, replacing the transformation of the current input image.

Load Deformation Field (Niftii): Load a probability maps deformation field saved in Nifti format, replacing the transformation of the current input image.

Load Deformation Field (Database): Load a probability maps deformation field saved in Database format, replacing the transformation of the current input image.

Load Inveon Shift: Read the image_ref_shift field from Inveon microPET files and apply it as transformation.
It is required for some versions of Inveon microPET for the alignment of the PET and CT images

Load Inverse of Inveon Shift: Read the image_ref_shift field from Inveon microPET files and apply the inverse as transformation. It is required for some versions of Inveon microPET for the alignment of the PET and CT images.

Combine Transformation: Load a transformation and combine it with the transformation of the current input image. Note that the combined transformation becomes the current one and can be inspected with the picture_7383.

Load to All Inputs: Load a transformation, replacing the transformation of all input images. This makes sense if all input images are in the same space, for instance for a set of parametric maps generated from a single series.

Combine with All Inputs: Load a transformation and combine it with the current transformation of each of the input images.

Each time after loading or combining transformations the images are resliced automatically.

The matching methods are described in the next sections.

Note: The performance of the automatic registration methods is highly dependent on the actual images to match!