Bimana

Package for performing automated bio-image analysis tasks.

Table of contents

1. Installation
2. Usage
3. License
4. Community Guidelines
5. Acknowledgements

Installation

Bimana can be installed on Linux, Windows (with 64 bit Python) & macOS and supports Python 3.10 and above. It is recommended to install and run Bimana within a virtual environment.

1. Download and install Python (Bimana was tested using Python version 3.10.6), Git and Git LFS. Linux and macOS users must also install libvips.

2. Launch the terminal (Linux and macOS users) or command prompt (Windows users). The proceeding commands will be entered into the opened window¹.

3. Create and activate a virtual environment called 'bimana-env' in your desired directory:

   pip install --upgrade pip

   python -m venv bimana-env

   . bimana-env/bin/activate (Linux and macOS users) or bimana-env\Scripts\activate.bat (Windows users)

4. Install PyTorch by specifying your system configuration using the official PyTorch get started tool and running the generated command:

   

   For example, according to the image above, Windows users without a GPU (i.e. CPU only) will run:

   pip3 install torch torchvision torchaudio

5. Clone this repository into your desired directory:

   git lfs install
   git clone https://github.com/AlphonsG/BIMANA.git
   

6. Navigate into the cloned directory:

   cd BIMANA

7. Install Bimana:

   git submodule update --init --recursive
   pip install -e .
   

Notes:

• ¹Confirm that the correct python version for Bimana has been installed using the python -V command in the terminal. If this command does not report the correct python version, try using the python3 -v command instead. If the second command produces the expected result, replace all python and pip commands in this guide with python3 and pip3, respectively.

• The virtual environment can be deactivated using:

  deactivate

Usage

Enter bimana -h or bimana --help within the bimana-env environment after installation for details on how to use Bimana.

Example commands that can be used to test Bimana using input data provided in each folder here are given below. After processing is finished for a given folder containing input images, multiple subfolders containing generated outputs (e.g. images, CSV files, etc) are created. Examples of these are also provided.

Example commands (first run cd misc from the cloned repository folder):

• Histological Section Analysis

  bimana histological-section-analysis ./examples/histological_section --staining-amount-in-tissue-area  --cilia-amount-above-tissue-area
  

• Tight junction analysis

  bimana tight-junction-analysis ./examples/tight_junctions  --analyse-tight-junctions --analyse-cells
  

• Live cell imaging metrics analysis

  bimana live-cell-imaging metrics-file-processing ./examples/live_cell_imaging
  

License

MIT License

Community guidelines

Guidelines for third-parties wishing to:

• Contribute to the software
• Report issues or problems with the software
• Seek support

can be found here.

Acknowledgements

• https://github.com/xavysp/DexiNed
• https://github.com/DevonsMo/IJOQ