table of contents
LIPSIA     Registration of 2D slices to a 3D anatomical data set
vreg3d
Registration rotates and shifts functional data into a standard coordinate frame, typically a Talairach-based stereotactic frame. This is done by aligning the functional data with a reference data set. The reference data set may be a high-resolution T1-weighted data set of the individual subject, or it can be an average data set obtained from averaging across a population of subjects. The functional data consist of a time sequence of 2D slices. For registration, the slices of one timepoint may be selected from this sequence and aligned with the reference data set. Alternatively, any other 2D slices that are in geometric alignment with the functional data slices may be used for registration. For instance, T1-high resolution slices are often obtained along with the functional scans. If these T1-slices are in geometric alignment (i.e. have the same orientation in space) then they may be used for registration instead of the functional slices. The rotational and translational parameters obtained from this operation are copied into a transformation matrix. In a subsequent step, this transformation matrix is then used to transform the remaining time steps or the zmap. The registration is done in three steps:

1. In the first step, we select a time step from the fMRT timecourse using 'vtimestep'. Note: This step is not needed, if T1-weighted 2D anatomical slices are used that are geometrically aligned with the functional data.

2. In the second step, we compute a transformation matrix that registers the 2D slices with the 3D data set using 'vreg3d'. This matrix describes a rigid, affine linear transformation using 3 translational and 3 rotational parameters.

3. In a third step, this transformation matrix is applied to the zmap, the anatomical slices, or the raw functional data. This is done by the program 'vdotrans', Optionally, you can also check the registration accuracy by applying the transformation to the 2D slices only, and comparing the result to the reference image in the data base.

Here are these steps in detail:

Identifying the reference image in the data base:
Caution: The instructions in the green box only hold on the intranet of the Max Planck Institute for Human Cognitiv and Brain Sciences in Leipzig. All other users may have a look in the WWW or any other resources to get an appropriate high resolution reference image.
You must first identify the high resolution reference image in the image data base to which your present image should be registered. The images in the data base have identification numbers. In order to obtain the data base id-number (the number) that belongs to your test subject, check the webpage https://newbdb.

Note that some test subjects have more than one reference image in the data base. In this case, you can choose either one.

Doing the registration:
The registration matrix describes a rigid, affine linear transformation between the 2D slices and the 3D reference image. The 2D slices must be in parallel and must have a fixed inter-slice distance. The matrix contains 3 translational and 3 rotational parameters. This matrix is computed using the program 'vreg3d'. It uses the 2D slices and optionally also 2D EPI-T1 slices to compute the transformation. Here is an example:

vtimestep -in functional_data.v -out tmp.v -step 0

vreg3d -in tmp.v -out transmatrix.v -ref reference_image.v -type MI

vdotrans -in tmp.v -out image.v -trans transmatrix.v -object all

vlv -in image.v reference_image.v

The first call selects a time step from the fMRT time course. In this example, the first step was selected. The subsequent call to 'vreg3d' uses this data for alignment with the reference image and places the transformation parameters into the matrix called 'transmatrix.v'. The parameter '-type' specifies the goal function to be used for alignment. If functional data are used (as in the above example) then mutual information (MI) is the best choice. If 2D anatomical slices are used then linear correlation is sufficient. The third call applies this matrix to the data and produces a rotated image of the functional data. The last call visualizes the results so that the registration accuracy can be checked.

The parameter '-pitch' can be used to specify an initial pitch angle. This angle is used as a starting point for the matching procedure. This can sometimes help to get better registration results, especially if the data set is not aligned with the CA/CP-axis. For example, if the data set is aligned with the Sylvian fissure, then use '-pitch -20', as the Sylvian fissure is usually tilted by an angle of approximately -20 degrees.

Refining the registration:
If there is an EPI-T1 scan available in addition to the MDEFT 2D slices, then this scan can be additionally used for registration in a refinement step. During refinement, new correlation values are computed, this time between the EPI-T1 slices and the reference data set. These correlation values are generally lower than the correlation values computed in the first step, however, this does not mean that the registration is less accurate.

In general:
The correlation values do not necessarily provide an indication for whether the registration was successful or not. The only way to be sure is to check the registration manually by applying the registration matrix to the 2D anatomical slices.

The EPI-T1 refinement can be enabled by setting '-refine true'. By default, EPI-T1 refinement is disabled.

Parameters of 'vreg3d':
-help
Prints usage information.
-in
Input file. Default: (none)
-out
Output file. Default: (none)
-ref
File containing 3D reference image. Required.
-band1
first band to be used for registration. Default: 0
-band2
last band to be used for registration. If not set or set to -1 all bands are used. Default: -1 (all bands).
-range [ 0 | 1 ]
Search range for shift and rotation parameters. (0=small, 1=big). Default: 0
-type [ corr | MI ]
Type of goal function. Possible values: linear correlation or mutual information). Default: corr
-angle
Inital pitch angle. Default: 0
-refine [ true | false ]
Whether to use additional data (e.g. EPI-T1) for refining the registration. Default: false


Max Planck Institute for Human Cognitive and Brain Sciences. Further Information: lipsia@cbs.mpg.de
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