azure / medical-imaging

ML-based medical imaging using Azure

Disclaimer
This code is provided for research and development use only. This code is not intended for use in clinical decision-making or for any other clinical use and the performance of the code for clinical use has not been established.

Medical Imaging with Azure Machine Learning Demos

Welcome to our medical imaging demo repository! The content includes several Python notebooks that cover medical imaging use cases based on classification, object detection and instance segmentation.

All use cases are based on publicly available datasets like brain RMI scans, cell micrographs, chest x-ray images and more. Since we cannot distribute the data directly, we refer to publicly available download locations.

The purpose of our notebooks is to demonstrate how Azure Machine Learning can be used to support medical imaging and other use cases in areas like data and model management, deployment, experiment tracking and explainability. Furthermore, we cover various data science approaches ranging from manual model development with PyTorch to automated machine learning for images. Another focus is to provide MLOPS based examples for automating the machine learning lifecycle for medical use cases including retraining when new data becomes available.

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.

medical-imaging's Issues

Server preparation

How to run this step:

Run provision script:
provision -p project.yml

Also where can I find the server and admin packages in this step: Copy server and admin packages to these folders ?

ModuleNotFoundError

from utils.demoutils import train, plot_learning_curve, to_categorical, predict_loader, inverse_normalize, plot_confusion_matrix throws a ModuleNotFoundError.

ModuleNotFoundError: No module named 'utils.demoutils'

I have tried:

1. pip install utils
2. pip install ivy-demo-utils

However, these do not resolve the issue. Can you point me to the library or module that is missing?

state Dictionary error while transfer learning

What does "server and adming packages" mean?

In /federated-learning/readme.md instructions chapter 3 there is a step that doesn't make sense for me.

Copy server and admin packages to these folders

I can't see any package/folder called server or admin into the repo, please be more specific here, I can't continue.