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.).
| Package | Tested version |
|---|---|
| matplotlib | 2.0.2 |
| NumPy | 1.13.1 |
| NiBabel | 2.1.0 |
| SciPy | 0.19.1 |
- 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
Visit our wiki to see alternative installation methods.
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