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Module category: Filter


The Registration module can registrate an image stack. It was created for processing together with the ReadITK module.


The module owns four ports for incoming and four ports for outgoing data. The first one delivers an uniform grid, the three following ports the RGB data.


The registration of an image stack can be modified by a few parameters:

You can choose the optimizertype out of a list. It is used to optimize the values of the metric. You can choose between:
MaxStepLength, MinStepLength, MinStepLengthDiv
The parameters of the optimizer modify the minimal and maximal step length, which are used for the search for the optimal metric value.
The metric quantitatively measures how well the images fits by comparing the gray-scale intensity of the images. You can choose between: The MeanSquaresImageToImageMetric computes the mean squared pixel-wise difference in intensity between the images. It relies on the assumption that intensity representing the same homologous point must be the same in both images. Hence, its use is restricted to images of the same modality. The MattesMutualInformationImageToImageMetric works with only one set of intensity samples, which is drawn from the images. This way it works much more faster.
The FillColor can be chosen between values of 0 (black) to 255 (white). With this color empty voxels are filled up, in case of transformation and/or rotation cause empty voxels.
The amount of the iterations of the registration can be restricted by this value.
You can choose the amount of levels for the image pyramid in addition to speed up the registration. With every level, the images are scaled to the half size based on the image pyramid level before.


Name Type Description
Optimizer Choice Optimizer type
MaxStepLength FloatScalar Maximum Step Length for Optimizer
MinStepLength FloatScalar Minimum Step Length for Optimizer
MinStepLengthDiv FloatScalar Minimum Step Length Divisor for higher Levels
Metric Choice Metric type
FillColor IntScalar Gray scale fill color for background of transformated images
Iterations IntScalar Number of Iterations
Pyramid IntScalar Number of Pyramidlevels

Input Ports

Name Type(s) Description
VolumeGridIn UniformGrid Grid
redin Float RGB - Red
greenin Float RGB - Green
bluein Float RGB - Blue

Output Ports

Name Type(s) Description
VolumeGridOut UniformGrid Grid
redout Float RGB - Red
greenout Float RGB - Green
blueout Float RGB - Blue


A "classical" combination for this module is the example Registration.net. A series of images is read in by ReadITK and aligned by Register. While the grid is directly lead to a collect module, an alpha channel is added to the RGB data by the module ColorDistance. After modification by the module Scalar2Vector, the data is lead to the Collect module, which delivers the volume data to a renderer.


Authors: Martin Aumüller, Ruth Lang, Daniela Rainer, Jürgen Schulze-Döbold, Andreas Werner, Peter Wolf, Uwe Wössner
Copyright © 1993-2016 HLRS, 2004-2014 RRZK, 2005-2014 Visenso
COVISE Version 2016.3