https://github.com/nvidia/clara-train-examples

Example notebooks demonstrating how to use Clara Train to build Medical Imaging Deep Learning models
https://github.com/nvidia/clara-train-examples

automl clara-train deep-learning healthcare-imaging medical-imaging-computing medical-imaging-processing python3 pytorch tcia-dac

Last synced: 16 days ago
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Example notebooks demonstrating how to use Clara Train to build Medical Imaging Deep Learning models

• Host: GitHub
• URL: https://github.com/nvidia/clara-train-examples
• Owner: NVIDIA
• License: apache-2.0
• Created: 2020-11-10T23:50:24.000Z (about 4 years ago)
• Default Branch: master
• Last Pushed: 2024-04-22T23:55:36.000Z (7 months ago)
• Last Synced: 2024-04-23T00:49:45.364Z (7 months ago)
• Topics: automl, clara-train, deep-learning, healthcare-imaging, medical-imaging-computing, medical-imaging-processing, python3, pytorch, tcia-dac
• Language: HTML
• Homepage:
• Size: 12.5 MB
• Stars: 119
• Watchers: 11
• Forks: 78
• Open Issues: 13
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Clara Train Examples

### Overview of Clara Train

Clara Train SDK is a domain optimized developer application framework that includes APIs for AI-Assisted Annotation, making any medical viewer AI capable and v4.1 enables a MONAI based training framework with pre-trained models to start AI development with techniques such as Transfer Learning, Federated Learning, and AutoML.

Clara Train has upgraded its underlying infrastructure from Tensorflow to MONAI. [MONAI](https://monai.io/) is an open-source, PyTorch-based framework that provides domain-optimized foundational capabilities for healthcare.

This repo contains Jupyter Notebooks to help you explore the features and capabilities of Clara Train, including AI-Assisted Annotation, AutoML, and Federated Learning.

## How to navigate this repository

#### PyTorch - Clara Train 4.1

If you're using Clara Train 4.1, you'll want to use the PyTorch folder structure.  You'll find the README.md and Welcome.ipynb files in the [PyTorch/Notebooks](PyTorch/NoteBooks) directory that will help you get started.

#### Tensorflow-Deprecated - Clara Train 3.1

If you're still using Clara Train 3.1, we encourage you to upgrade to [Clara Train 4.1](https://ngc.nvidia.com/catalog/containers/nvidia:clara-train-sdk). You can find information on converting your current Clara 3.1 MMAR's to [Clara 4.0 compatible MMAR's on our docs](https://docs.nvidia.com/clara/clara-train-sdk/pt/appendix/migration_from_tf.html#migratefromtf).

If you're still interested in exploring Clara Train 3.1 using our old Jupyter Notebooks, you'll now find them under the Tensorflow-Deprecated folder.  You'll find all of the instructs in the README.me file.