rescale4dl 0.1.1

My python package package

ReScale4DL: Balancing Pixel and Contextual Information for Enhanced Bioimage Segmentation

A systematic approach for determining optimal image resolution in deep learning-based microscopy segmentation, balancing accuracy with acquisition/storage costs.

Key Features

• Resolution simulation: Rescale images and their respective annotations (upsample and downsample)
• Segmentation evaluation: Compare performance across resolutions using:
  • Mean Intersection-over-Union (IoU)
  • Morphological features
  • Potential throughput
  • Personalised metrics
• Visualization tools: Generate comparative plots and sample outputs

Installation

ReScale4DL is available as a Python package through pip. Activate your conda environment or create one and install it with pip:

pip install rescale4dl

Manual installation

Manual installation from using GitHub repository

git clone https://github.com/HenriquesLab/ReScale4DL.git
cd rescale4dl
conda create -n rescale4dl "python<=3.12"
conda activate rescale4dl
python -m pip install .

Usage

1. Image Rescaling

Notebook: Rescale_Images.ipynb

2. Segmentation Analysis

Notebook: Evaluate_Segmentation.ipynb

3. Rescale and crop

Notebook: Rescale_Foundation_Models.ipynb

Contributing

We welcome contributions through:

• Issue reporting
• Pull requests

License

MIT License - See LICENSE for details

Citation

If using this work in research, please cite:

@article{gferreira2025rescale4dl,
  title={ReScale4DL: Balancing Pixel and Contextual Information for Enhanced Bioimage Segmentation},
  author={Ferreira, Mariana G. and Saraiva, Bruno M. and Brito, Antonio D. and Pinho, Mariana G. and Henriques, Ricardo and G{\'o}mez-de-Mariscal, Estibaliz },
  journal={bioRxiv},
  year={2025},
  publisher = {Cold Spring Harbor Laboratory},
  URL = ,
  eprint = ,
}