Registration CLP

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Co-Register

General Information

  • Type: CLP
  • Category: Registration
  • Author: Gemma Piella
  • Contributor: Héctor Fernández
  • Contact: hector.fernandez@upf.edu
  • Description: Calculates the transformation needed for moving a set temporally related images to a reference image.

Usage

A set of temporally related vtk images is needed for using this command line plugin. The user can select the type of metric to make the registration and the temporal position of the image he wants to select as reference, usually the image placed at t = 0 is used as reference.

The command line plugin produces two different outputs, a transformation file ".dof" saved in Tranformation saved file, this transformation can't be shown in GIMIAS. The other output is the set of vtk's images with the transformation applied.

Inputs:

    • Input Image: set of 3D vtk images temporally related.
    • Fixed Mask Image: region on which the algorithm selects the points to make co-registration. The number of points is defined by the parameter Number Of Samples. It is an optional input.
    • Moving Mask Image: movement region, all the triangle in the above image.
    • Transformation: input transformation that can be applied to the set of images. It is an optional input.

Parameters

  • Output File Parameters
    • Tranformation saved file: file root to save the transformation from registration algorithms (ex: c:/Temp/transform.dof)
  • Registration Parameters
    • Metric Options: type of metric to calculate registration.
      • Default: image placed at reference time is taken as reference
      • Sequential: each image is taken as a reference of the next one (image1 reference image2, image2 reference image3).
      • Dense: mix between previous metrics.
    • Number Of Samples: Number of aleatory points select on image for registration.
    • Sequential Weigth metric: used for dense metric, weigth between sequential and default metric.
    • Reference Time: time position of image taken as a reference
    • TimeStep: separation between two consecutive images, the value choose is the inverse (i.e. a TimeStep = 2.5 means a temporal separation between images of 0.5 time units)
    • MinTimeStep: minimun time separation between consecutive frames, it is use the inverse of the value.


Examples

CT

CoRegister Steps
CoregisterWF1.png
CoregisterWF2.png
CoregisterWF3.png
CoregisterWF4.png

Development

Source code: C++ Source code and XML description

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