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Utilities for compressing multiphoton calcium imaging movies and stacks

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compress-multiphoton

Most labs store raw data uncompressed resulting in excessive data storage requirements and data transfer times. Here we coordinate efforts for adopting data compmression methods for multiphoton imaging of calcium and voltage signals and 3D stacks. We invite all to critique and contribute to this project.

Aims

We aim to introduce effectively lossless methods for data compression. Scientists should be able trust the method to preserve all biologically relevant information even when the compression does not preserve a bit-for-bit match to the acquired data.

The Compression.ipynb notebook derives the lossless compression scheme aiming to achieve 4:1 - 6:1 compression ratio for typical imaging scenarios.

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  • Jupyter Notebook 98.2%
  • Python 1.8%