ivadomed is an integrated framework for medical image analysis with deep learning, based on PyTorch. The name is a portmanteau between IVADO (The Institute for data valorization) and Medical.

If you use ivadomed for your research, please cite our paper:

@article{gros2021ivadomed,
  doi = {10.21105/joss.02868},
  url = {https://doi.org/10.21105/joss.02868},
  year = {2021},
  publisher = {The Open Journal},
  volume = {6},
  number = {58},
  pages = {2868},
  author = {Charley Gros and Andreanne Lemay and Olivier Vincent and Lucas Rouhier and Marie-Helene Bourget and Anthime Bucquet and Joseph Paul Cohen and Julien Cohen-Adad},
  title = {ivadomed: A Medical Imaging Deep Learning Toolbox},
  journal = {Journal of Open Source Software}
}

Home

Overview

• Purpose
• Technical features
• Use cases

Getting started

• Installation
• Data
• Configuration File
• Usage
• Architectures
• Pre-trained models
• Scripts
• Help

Tutorials

• One-class segmentation with 2D U-Net
• Cascaded architecture
• Estimate uncertainty
• Optimize Hyperparameters
• Two-class microscopy segmentation with 2D U-Net

Developer section

• Contributing to ivadomed
• API Reference
• Contributors
• License