ROIExtractors

Automatically read optical imaging/segmentation data into a common API

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Table of Contents

• About
• Installation
• Documentation
• Funding
• License

About

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()

Installation

To install the latest stable release of roiextractors though PyPI, type:

pip install roiextractors

For 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@main

Documentation

See our ReadTheDocs page for full documentation, including a gallery of all supported formats.

Funding

ROIExtractors is funded by

• Stanford University as part of the Ripple U19 project (U19NS104590).
• LBNL as part of the NWB U24 (U24NS120057).

License

ROIExtractors is distributed under the BSD3 License. See LICENSE for more information.