SIMA (Sequential IMage Analysis) is an Open Source package for analysis of time-series imaging data arising from fluorescence microscopy. The functionality of this package includes:
- correction of motion artifacts
- segmentation of imaging fields into regions of interest (ROIs)
- extraction of dynamic signals from ROIs
The included ROI Buddy software provides a graphical user interface (GUI) supporting the following functionality:
- manual creation of ROIs
- editing of ROIs resulting from automated segmentation
- registration of ROIs across separate imaging sessions
For complete documentation go to <http://www.losonczylab.org/sima>
- Python 2.7
- numpy >= 1.6.2
- scipy >= 0.13.0
- matplotlib >= 1.2.1
- scikit-image >= 0.9.3
- shapely >= 1.2.14
- OpenCV >= 2.4.8, required for segmentation, registration of ROIs across multiple datasets, and the ROI Buddy GUI
- scikit-learn >= 0.11, required for stICA segmentation
- h5py >= 2.3.1, required for HDF5 file format
- pylibtiff, required for more efficient handling of large TIFF files
- bottleneck >=0.8 , for faster performance
- mdp, required for ICA demixing of channels
If you build the package from source, you may also need:
If you use SIMA for your research, please cite the following paper in any resulting publications:
Unless otherwise specified in individual files, all code is
Copyright (C) 2014 The Trustees of Columbia University in the City of New York.
This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/>.