Modules:PlastimatchLANDWARP

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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. 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.

Usability issues

Please report usability issues to the bug tracker.

• http://forge.abcd.harvard.edu/gf/project/plastimatch/tracker/?action=TrackerItemBrowse&tracker_id=450

Source code & documentation

We recommended to download the latest source code from subversion:

• Project page
• Source download (svn access)

Documentation:

• http://plastimatch.org

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.