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Explore and annotate your multi-channel large TIF files with this user-friendly viewer.

Project description

ImmunoViewer

Explore and annotate your multi-channel, large TIF files with this user-friendly viewer designed for high-resolution multiplex imaging.

Table of Contents

About ImmunoViewer

ImmunoViewer is designed to efficiently handle high-resolution multiplex imaging files, such as those generated by Orion Rarecyte or Keyence Immuno Fluorescence scanners. It supports multi-channel images and allows users to add annotations, customize colors, and adjust signal intensities for each channel. Your suggestions for additional features are highly welcomed!

ImmunoViewer Screenshot

Installation

ImmunoViewer requires Python 3.10 or higher. We recommend installing ImmunoViewer within a Python virtual environment to manage dependencies effectively.

Using venv

python -m venv /path/to/new/virtual/environment
source /path/to/new/virtual/environment/bin/activate

Using Conda

conda create -n ImmunoViewer
conda activate ImmunoViewer

Install from GitHub

git clone https://github.com/davidvi/ImmunoViewer.git
cd ImmunoViewer
pip install .

Install from pip

pip install ImmunoViewer

Usage

Folder Structure

Configure your data directory to manage input and output files efficiently:

data_directory/
  sample1.ome.tiff
  sample2/
    dapi.tiff
    CD68.tiff

Files are automatically processed and stored in a separate 'processed' directory.

Generate Tiles

Generate image tiles for easier viewing and processing:

ImmunoViewerWatch [data_directory] [processed_directory]

Run the Viewer

Launch the viewer server with the following command:

ImmunoViewerServe --port [port (default is 8000)] --host [IP address (default = 0.0.0.0)] [processed_directory]

Access the viewer by navigating to http://[IP address]:[port] in your web browser. Note: If you use the default IP address (0.0.0.0), ensure the port is properly secured if exposed over the network.

Cloud deploy

See instructions in folder cloud-deploy.

Acknowledgements

ImmunoViewer uses OpenSeadragon for robust, high-performance image visualization.

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