Spheroid Analysis with micro-sam

This repository contains scripts for analysis of spheroids using micro-sam.

Requirements

• Fiji/ImageJ
• Python 3.8+
• CUDA-capable GPU (recommended)
• Conda package manager

Scripts and Files

• fiji_scripts/convert_RGB_to8bit_.ijm
  • Fiji script used to preprocess data micro-sam which requires 8-bit images as input for the fine-tuning
• fiji_scripts/Make_overlays_labelMap_.ijm
  • Fiji script to convert label maps to Fiji ROIs and overlay images from a set of images.
• fiji_scripts/Make_PDX_montages_.ijm
  • Fiji script to make a image montage of images in batch
• python_scripts/randomImages.py
  • Python script to extract random images from the data sets for training micro-sam
• notebooks/sam_finetuning.ipynb
  • Jupyter notebook which contains all code for fine-tuning of our spheroid segmentation models, run prediction on the data sets and accompanying script to extract measurements from. Based on the notebook at the micro-sam repository: https://github.com/computational-cell-analytics/micro-sam/blob/master/notebooks/sam_finetuning.ipynb.
• environment.yml
  • Conda environment file used to run the jupyter notebook

To initiate the conda environment based on the environment.yml file, use the following command:

conda env create -f environment.yml -n micro-sam
conda activate micro-sam
jupyter notebook

Contact

For questions concerning the code please reach out to Maarten Paul (maarten.paul@gmail.com)

Citation

If you use this code in your research, please cite:

License

This project is licensed under the MIT License - see the LICENSE file for details.