Difference between revisions of "Modules:PlastimatchLANDWARP"

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|[[Image:plastimatch_image_1.png|thumb|280px|Before Registration]]
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|[[Image:before_reg.png|thumb|280px|Before Registration]]
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|[[Image:3D_Slicer_Plastimatch_Landmark_Registration_Tutorial.png|thumb|280px|[http://forge.abcd.harvard.edu/gf/download/frsrelease/110/1622/3D_Slicer_Plastimatch_Landmark_Registration_Tutorial.ppt Download tutorial]]]
 
|[[Image:3D_Slicer_Plastimatch_Landmark_Registration_Tutorial.png|thumb|280px|[http://forge.abcd.harvard.edu/gf/download/frsrelease/110/1622/3D_Slicer_Plastimatch_Landmark_Registration_Tutorial.ppt Download tutorial]]]
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|[[Image:plastimatch_tutorial_data.png|thumb|230px|[http://forge.abcd.harvard.edu/gf/download/frsrelease/85/1619/synthetic_img.zip Download tutorial data]]]
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|[[Image:fixed.png|thumb|230px|[http://forge.abcd.harvard.edu/gf/download/frsrelease/85/1619/synthetic_img.zip Download tutorial data]]]
 
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** '''Basis function:''' Here you can choose either tps (thin plate splines), or gauss (Gaussian RBF), or wendland (Wendland RBF).
 
** '''Basis function:''' Here you can choose either tps (thin plate splines), or gauss (Gaussian RBF), or wendland (Wendland RBF).
 
** '''RBF radius:''' Here you can choose the radius of RBF.
 
** '''RBF radius:''' Here you can choose the radius of RBF.
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** '''Stiffness:''' Here you can choose the regularization coefficient.
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** '''Number of clusters:''' Here you can choose the number of landmark clusters.
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** '''Stiffness:''' Here you can choose the regularization parameter.
 
** '''Default Pixel Value:''' Here you can choose the value for pixels with unknown value.
 
** '''Default Pixel Value:''' Here you can choose the value for pixels with unknown value.
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|[[Image:plastimatch_landmark_gui.png|thumb|280px|User Interface]]
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== Development ==
 
== Development ==
  
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===References===
 
===References===
 
* G Sharp et al. "Plastimatch - An open source software suite for radiotherapy image processing," Proceedings of the XVIth International Conference on the use of Computers in Radiotherapy, May, 2010.
 
* G Sharp et al. "Plastimatch - An open source software suite for radiotherapy image processing," Proceedings of the XVIth International Conference on the use of Computers in Radiotherapy, May, 2010.
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* N. Shusharina, G. Sharp "Landmark-based image registration with analytic regularization", IEEE Trans. Med. Imag., submitted
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* N. Shusharina, G. Sharp "Landmark-based image registration with analytic regularization", IEEE Trans. Med. Imag., submitted, 2011.

Latest revision as of 23:16, 14 February 2011

Home < Modules:PlastimatchLANDWARP

Return to Slicer 3.6 Documentation


Plastimatch > Landmark-based Registartion

Before Registration
After Registration

General Information

Module Type & Category

Type: CLI

Category: Plastimatch

Authors, Collaborators & Contact

  • Authors: See COPYRIGHT.TXT contained within the package
  • Contact: Nadya Shusharina, Department of Radiation Oncology, Massachusetts General Hospital (nshsuharina@partners.org)
  • Web page: http://plastimatch.org

Module Description

This is the plastimatch landmark-based deformable image registration module. The intended application of this method is rapid, interactive correction of registration failures with a small number of mouse clicks. Compared to other landmark-based methods, the plastimatch registration method might offer:

  1. both local and global registration
  2. regularization of the deformation field

Examples of how this module is being used:

  • Intra-subject registration for adaptive radiotherapy
  • Inter-subject registration for automatic segmentation

Usage

Tutorials

Download tutorial
Download tutorial data

Quick Tour of Features and Use

  • Input/Output panel:
    • Fixed Volume: Here you choose the "fixed image", which is the reference image.
    • Moving Volume: Here you choose the "moving image", which will be warped to match the fixed image.
    • Output Volume: Here you choose where to put the warped image. You can replace an existing image in the scene, or create a new image.
    • Basis function: Here you can choose either tps (thin plate splines), or gauss (Gaussian RBF), or wendland (Wendland RBF).
    • RBF radius: Here you can choose the radius of RBF.
    • Number of clusters: Here you can choose the number of landmark clusters.
    • Stiffness: Here you can choose the regularization parameter.
    • Default Pixel Value: Here you can choose the value for pixels with unknown value.
User Interface

Development

Notes from the Developer(s)

Developer-oriented documentation is found on the plastimatch web site: http://plastimatch.org

Dependencies

This module has no dependencies.

Tests

Plastimatch features approximately 100 test cases.

Known bugs

Usability issues

Please report usability issues to the bug tracker.

Source code & documentation

We recommended to download the latest source code from subversion:

Documentation:

More Information

About plastimatch

Plastimatch is an open source software for deformable image registration. It is designed for high-performance volumetric registration of medical images, such as X-ray computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). Software features include:

  • B-spline method for deformable image registration (GPU and multicore accelerated)
  • Demons method for deformable image registration (GPU accelerated)
  • ITK-based algorithms for translation, rigid, affine, demons, and B-spline registration
  • Pipelined, multi-stage registration framework with seamless conversion between most algorithms and transform types
  • Landmark-based deformable registration using thin-plate splines for global registration
  • Landmark-based deformable registration using radial basis functions for local corrections
  • Broad support for 3D image file formats (using ITK), including Dicom, Nifti, NRRD, MetaImage, and Analyze
  • Dicom and DicomRT import and export
  • XiO import and export
  • Plugins for 3D Slicer

Plastimatch also features two handy utilities which are not directly related to image registration:

  • FDK cone-beam CT reconstruction (GPU and multicore accelerated)
  • Digitally reconstructed radiograph (DRR) generation (GPU and multicore accelerated)

Acknowledgment

National Institutes of Health
NIH / NCI 6-PO1 CA 21239
Federal share of program income earned by MGH on C06CA059267

Progetto Rocca Foundation
A collaboration between MIT and Politecnico di Milano

References

  • G Sharp et al. "Plastimatch - An open source software suite for radiotherapy image processing," Proceedings of the XVIth International Conference on the use of Computers in Radiotherapy, May, 2010.
  • N. Shusharina, G. Sharp "Landmark-based image registration with analytic regularization", IEEE Trans. Med. Imag., submitted, 2011.
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