Modules:DeformableB-SplineRegistration-Documentation-3.6

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Gallery of New Features

Module Name

Deformable B-Spline Registration

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  Data set that was to be deformed

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  Data set after b-Spline with wrong parameters

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General Information

This module was implemented by Jim Miller and Bill Lorensen and is based on the ITK B-spline implementation.

Module Type & Category

Type: CLI

Category: Base or (Filtering, Registration, etc.)

Authors, Collaborators & Contact

• Author: Bill Lorensen
• Contact: bill.lorensen at gmail.com

Module Description

Overview of what the module does goes here.

Usage

• Parameters:
  • Iterations: Number of iterations to run the optimization method to estimate the registration parameters.
  • Grid Size: Number of grid points on interior of the fixed image. Larger grid sizes allow for finer registrations.
    • You can use this module to manually run a multiresolution registration by starting with a coarse grid, creating a resampled volume, and passing that resampled volume as the moving image for the next run with a finer grid.
    • Make sure you hit the tab key when changing the grid size.
  • Histogram bins: Number of histogram bins to use for Mattes Mutual Information. Reduce the number of bins if a deformable registration fails. If the number of bins is too large, the estimated PDFs will be a field of impulses and will inhibit reliable registration estimation.
  • Spatial samples: Number of spatial samples to use in estimating Mattes Mutual Information. Larger values yield more accurate PDFs and improved registration quality.
  • Constrain deformation: Constrain the deformation to the amount specified in Maximum Deformation
  • Maximum deformation: If Constrain Deformation is checked, limit the deformation to this amount.
  • Default pixel value: Default pixel value used if resampling a pixel outside of the volume.
• IO
  • Intial Transform: Initial transform for aligning the fixed and moving image. Maps positions in the fixed coordinate frame to positions in the moving coordinate frame. This transform should be an affine or rigid transform. It is used an a bulk transform for the BSpline. Optional.
  • Fixed image: Fixed image to which to register
  • Moving image: Image to register to the fixed image
  • Output transform: Transform calculated that aligns the fixed and moving image. Maps positions from the fixed coordinate frame to the moving coordinate frame. Optional (specify an output transform or an output volume or both).
  • Output Volume: Resampled moving image to fixed image coordinate frame. Optional (specify an output transform or an output volume or both).
• click Apply

• Be careful how you set the parameters

Examples, Use Cases & Tutorials

The BSpline registration module is used in the following examples of the |Registration Case Library. Each case contains a step-by-step tutorial incl. parameter selections/presets. DWI alignment: align DTI volume with structural reference scan (T2)

• Probabilistic Tissue Atlas Case 10: Segmentation via co-registered probabilistic tissue atlas
• RegLib 03: DTI alignment Case 03: DWI alignment: align DTI volume with structural reference scan (T2)
• RegLib 06: Breast MRI follow-up Case 06: Breast MRI follow-up pre/post treatment with contrast enhancement and strong intensity inhomogeneity
• Case 08: Intra-subject PET-CT scan. Two exams each with a co-registered PET-CT dataset.

Quick Tour of Features and Use

List all the panels in your interface, their features, what they mean, and how to use them. For instance:

• Input panel:
• Parameters panel:
• Output panel:
• Viewing panel:

Development

Dependencies

Other modules or packages that are required for this module's use.

Known bugs

Follow this link to the Slicer3 bug tracker.

Usability issues

Follow this link to the Slicer3 bug tracker. Please select the usability issue category when browsing or contributing.

Source code & documentation

Source Code: [1]

Documentation: doxygen

More Information

Acknowledgment

This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Information on the National Centers for Biomedical Computing can be obtained from National Centers for Biomedical Computing.