Segmentator is a free and open-source package for multi-dimensional data exploration and segmentation for 3D images. This application is mainly developed and tested using ultra-high field magnetic resonance imaging (MRI) brain data.

The goal is to provide a complementary tool to the already available brain tissue segmentation methods (to the best of our knowledge) in other software packages (FSL, Freesurfer, SPM, Brainvoyager, itk-SNAP, etc.).

• Our preprint can be accessed from this link.
• Released versions of this package can be cited by using our Zenodo DOI.

Python 2.7

• Make sure you have Python 2.7 and pip installed.
• Download the latest release and unzip it.
• Change directory in your command line:

cd /path/to/segmentator

• Install the requirements by running the following command:

pip install -r requirements.txt

• Install Segmentator:

python setup.py install

• Simply call segmentator with a nifti file:

segmentator /path/to/file.nii.gz

• Or see the help for available options:

segmentator --help

Check out our wiki for further details such as GUI controls, alternative installation methods and more...

Please use GitHub issues for questions, bug reports or feature requests.

Copyright © 2016, Omer Faruk Gulban and Marian Schneider. Released under GNU General Public License Version 3.

This application is based on the following work:

• Kindlmann, G., & Durkin, J. W. (1998). Semi-automatic generation of transfer functions for direct volume rendering. In Proceedings of the 1998 IEEE symposium on Volume visualization - VVS ’98 (pp. 79–86). New York, New York, USA: ACM Press. http://doi.org/10.1145/288126.288167
• Kniss, J., Kindlmann, G., & Hansen, C. (2001). Interactive volume rendering using multi-dimensional transfer functions and direct manipulation widgets. In Proceedings Visualization, 2001. VIS ’01. (pp. 255–562). IEEE. http://doi.org/10.1109/VISUAL.2001.964519
• Kniss, J., Kindlmann, G., & Hansen, C. (2002). Multidimensional transfer functions for interactive volume rendering. IEEE Transactions on Visualization and Computer Graphics, 8(3), 270–285. http://doi.org/10.1109/TVCG.2002.1021579
• Kniss, J., Kindlmann, G., & Hansen, C. D. (2005). Multidimensional transfer functions for volume rendering. Visualization Handbook, 189–209. http://doi.org/10.1016/B978-012387582-2/50011-3
• Jianbo Shi, & Malik, J. (2000). Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8), 888–905. http://doi.org/10.1109/34.868688
• Ip, C. Y., Varshney, A., & Jaja, J. (2012). Hierarchical exploration of volumes using multilevel segmentation of the intensity-gradient histograms. IEEE Transactions on Visualization and Computer Graphics, 18(12), 2355–2363. http://doi.org/10.1109/TVCG.2012.231