CASToR - Customizable and Advanced Software for Tomographic Reconstruction

CASToR is an open-source multi-platform project for 4D emission (PET and SPECT) and transmission (CT) tomographic reconstruction. This platform is a scalable software providing both basic image reconstruction features for "standard" users and advanced tools for specialists in the reconstruction field, to develop, incorporate and assess their own methodologies in image reconstruction (such as specific projectors, optimization algorithms, dynamic data modeling, etc) through the implementation of new classes.

A generic and flexible input data file format has been designed in order to incorporate all information needed for the reconstruction, whatever the modality and the data format (list-mode or histogram). Being strictly a reconstruction software, and due to its generic design, CASToR will not estimate corrections specific to each data channel (namely normalization, attenuation, scatters and randoms), so all these corrections should be pre-computed and embedded in the data file.

Our aim is to design a generic core algorithm flexible enough to cope with the particularities of each imaging modality through a user-friendly class system allowing for the integration of new methodologies.

The current version (1.0) of the platform includes:

  • Iterative reconstruction algorithms.
  • PET and SPECT (parallel-hole and convergent-beam collimators) geometries
  • Reconstruction of multi-frames and respiratory/cardiac gated acquisitions.
  • Projector plug-in class system, including original [1] and accelerated [2] versions of the Siddon and Joseph [3] projectors.
  • Optimization algorithm plug-in class system, including MLEM [4], NEGML [5], AML (AB-EMML) [6] and Landweber [7] optimization algorithms.
  • Plug-in class systems for image convolution and spatial regularization, and general image processing.
  • Two-level parallel CPU implementation using MPI (multi-computers) and openMP (multi-threads) libraries.
  • Interfile I/O format for images.
  • Utility tool to convert GATE [8] Monte Carlo simulated data in ROOT format [9] into the CASToR datafile format.


To download the CASToR source code, please first fill-in the registration form.


Comprehensive information about CASToR classes, architecture, plug-in system and data file formats can be found in the documentation section.

Benchmarks scripts and datasets to check your CASToR installation can be downloaded from the benchmarks section.

Datafile converters for one Siemens PET system can be found in the data converters section. This page will be updated as converters for other systems become available.

If you encounter any difficulties using CASToR, please send a mail describing the issue to the mailing-list.




[1] RL Siddon. "Fast calculation of the exact radiological path for a three-dimensional CT array". Med Phys. 1985 Mar-Apr;12(2):252-5.

[2] Filip Jacobs, et al. "A Fast Algorithm to Calculate the Exact Radiological Path Through a Pixel Or Voxel Space". Journal of Computing and Information Technology 6(1) · December 1998

[3] Joseph PM. "An Improved Algorithm for Reprojecting Rays through Pixel Images". IEEE Trans Med Imaging. 1982;1(3):192-6.

[4] L. A. Shepp and Y.Vardi, "Maximum likelihood reconstruction for emission tomography" IEEE Trans. Med. Imaging, vol. MI-1, pp. 113–122, 1982.

[5] Katrien Van Slambrouck , Simon Stute , Claude Comtat , Merence Sibomana , Floris H. P. van Velden , Ronald Boellaard , Johan Nuytset al . "Bias reduction for low-statistics PET: Maximum likelihood reconstruction with modified Poisson distribution". IEEE TMI, Jan 2015, vol. 34, pp. 126-136

[6] C. Byrne, "Iterative algorithms for deblurring and deconvolution with constraints" Inverse Problems, 1998, vol. 14, pp. 1455-67

[7] L. Landweber "An Iteration Formula for Fredholm Integral Equations of the First Kind" American Journal of Mathematics, Vol. 73, No. 3 (Jul., 1951), pp. 615-624

[8] Jan S, et al. "GATE: a simulation toolkit for PET and SPECT". Phys. Med. Biol. 49 (2004) 4543-4561