ROIExtractors provides a common API for various optical imaging and segmentation formats to streamline conversion and data analysis. ROI stands for Region Of Interest, which is the region in a set of acquired fluorescence images which the segmentation software has determined as a neuron.
Features:
- Reads data from 10+ popular optical imaging and segmentation data formats into a common API.
- Extracts relevant metadata from each format.
- Provides a handy set of methods to analyze data such as
get_roi_locations()
To install the latest stable release of roiextractors though PyPI, type:
pip install roiextractorsFor more flexibility we recommend installing the latest version directly from GitHub. The following commands create an environment with all the required dependencies and the latest updates:
git clone https://github.com/catalystneuro/roiextractors
cd roiextractors
conda env create roiextractors_env
conda activate roiextractors_env
pip install -e .Note that this will install the package in editable mode.
Finally, if you prefer to avoid conda altogether, the following commands provide a clean installation within the current environment:
pip install git+https://github.com/catalystneuro/roiextractors.git@mainSee our ReadTheDocs page for full documentation, including a gallery of all supported formats.
ROIExtractors is funded by
- Stanford University as part of the Ripple U19 project (U19NS104590).
- LBNL as part of the NWB U24 (U24NS120057).
ROIExtractors is distributed under the BSD3 License. See LICENSE for more information.