DICOMautomaton is a collection of software tools for processing and analyzing medical images.
Once a workflow has been developed, the aim of DICOMautomaton is to require minimal interaction. However, some
interactive tools are included for developing a workflow, exploratory analysis, and contouring.
DICOMautomaton is meant to be flexible enough to adapt to a wide variety of situations and has been incorporated into projects to provide: a local PACS, kinetic modeling of perfusion images, automated fuzzy mapping of ROI names to a standard lexicon, dosimetric analysis, TCP and NTCP modeling, ROI contour/volume manipulation, estimation of surface dose, ray casting through patient and phantom geometry, rudimentary linac beam optimization, radiomics, and has been used in various ways to explore the relationship between toxicity and dose in sub-organ compartments.
DICOMautomaton relies only on open source software and is itself open source software.
Source code is available here.
Currently, binaries are not provided. Only linux is supported and a recent C++ compiler is needed. A PKGBUILD is provided for Arch Linux and derivatives, and CMake can be used to generate deb files for Debian derivatives. A docker container is available for easy portability to other systems. DICOMautomaton has successfully run on x86, x86_64, and most ARM systems. To maintain flexibility, DICOMautomaton is generally not ABI or API stable.
Please send questions or comments to . Or, even better, send a pull request ☺.
Q. What is the best way to use DICOMautomaton?
A. DICOMautomaton provides a command-line interface, SFML-based image viewer, and limited web interface. The command-line interface is most conducive to automation, the viewer works best for interactive tasks, and the web interface works well for specific installations.
Q. How do I contribute?
Q. Where do I send bug reports?
Q. How do I contact the author?
A. Please send all thoughts, patches, suggestions, and notes to .
Several publications and presentations refer to DICOMautomaton or describe some aspect of it. Here are a few:
H. Clark, J. Beaudry, J. Wu, and S. Thomas.
Making use of virtual dimensions for visualization and contouring.
Poster presentation at the International Conference on the use of Computers in Radiation Therapy, London, UK. June 27--30, 2016.
H. Clark, S. Thomas, V. Moiseenko, R. Lee, B. Gill, C. Duzenli, and J. Wu.
Automated segmentation and dose-volume analysis with DICOMautomaton.
In the Journal of Physics: Conference Series, vol. 489, no. 1, p. 012009. IOP Publishing, 2014.
H. Clark, J. Wu, V. Moiseenko, R. Lee, B. Gill, C. Duzenli, and S. Thomas.
Semi-automated contour recognition using DICOMautomaton.
In the Journal of Physics: Conference Series, vol. 489, no. 1, p. 012088. IOP Publishing, 2014.
H. Clark, J. Wu, V. Moiseenko, and S. Thomas.
Distributed, asynchronous, reactive dosimetric and outcomes analysis using DICOMautomaton.
Poster presentation at the COMP Annual Scientific Meeting, Banff, Canada. July 9--12, 2014.
If you use DICOMautomaton in an academic work, we ask that you please cite the most relevant publication for that work.