An Open-Source Cone-Beam CT Reconstruction Tool
                                                               for Imaging Research

OSCaR (Open Source Cone-beam Reconstructions) is a GUI (Graphical User Interface) developed for computing
three-dimensional reconstructions from data gathered from cone-beam x-ray CT scanning geometries. The
package is implemented in Matlab with the intention of being portable across many computerUT Crest architectures
and easy to use.

GUI of the Reconstruction Stage

  • Download OSCaR

    Right now OSCaR is in the beta-testing stage. You can download "OSCaR-02" here (Updated December 2008).

  • Motivation and Purpose

    The Feldkamp-Davis-Kress (FDK) reconstruction framework for 3D cone-beam CT reconstruction has been known since 1984. However, the lack of availability of practical, flexible, free FDK software implementations often hampers medical physics researchers and inhibits multi-institutional research collaboration. Recognizing the need for common, reference-able imaging research software, the American Association for Physicists in Medicine (AAPM) Imaging Research Subcommittee has supported the development of "OSCaR", an open-source Matlab implementation of CBCT reconstruction for free distribution as a research tool by the AAPM. The goal is to offer a straightforward, open source code and GUI implementation that emphasizes flexibility, generality, and ease of use. The implementation has a transparent interface for 3D image reconstruction with the intention of providing a useful base platform for developing advanced techniques (e.g., artifact correction) or for conducting image quality studies (e.g., selection of optimal reconstruction filters). Some simple test image data is also included. The code is intended for research use, rather than clinical or commercial implementation.

  • Methods and Materials

    Broadly speaking, OSCaR consists of three main stages: pre-processing, reconstruction, and export. In the pre-processing stage, CBCT data is parsed from a broad, general base of standard data-file formats (e.g., DICOM, binary, JPEG, TIFF, PNG, etc.). Geometric corrections, pixel aperture, sampling, air normalization, and other device-dependent parameters associated with the projection data are applied. In the reconstruction stage, OSCaR permits the specification of a Field-Of-View (FOV), voxel size, and reconstruction filters. The actual voxel-driven reconstruction uses the well-known FDK filtered back-projection algorithm. In the export stage the reconstructed data and the maximum/minimum of the reconstructed volume can be saved in a *.mat file.

    Although compiled software is certainly faster than interpreted Matlab code, a Matlab implementation circumvents the use of custom compilation libraries. The result is a software tool that is easy to use and can be rapidly adapted and modified for new research purposes. In accordance with the desires of the AAPM Imaging Research Subcommittee, OSCaR  will be made freely available on the AAPM web-site to members of the AAPM for research in algorithm development, CBCT image quality, and multi-institutional collaboration.

    - This work was supported by the AAPM Imaging Research Subcommittee, MITACS and Princess Margaret Hospital.

    Back to my home page