# MONAI in JupyterLab

Medical Open Network for AI ([MONAI](https://project-monai.github.io/)) is a framework built for deep learning in healthcare imaging. To use MONAI on the DNAnexus Platform, [run JupyterLab](/user/jupyter-notebooks/running-dxjupyterlab.md#running-from-the-ui) with the `MONAI_ML` feature, which includes:

* [MONAI Core](https://project-monai.github.io/core.html): PyTorch-based framework for deep learning in healthcare imaging.
* [MONAI Label](https://project-monai.github.io/label.html): An intelligent image labeling and learning tool designed to create training datasets and build AI annotation models. It provides a server-client framework that integrates with imaging viewers.
* [3D Slicer](https://www.slicer.org/): An open-source software designed for the visualization, processing, and analysis of medical, biomedical, and other 3D images. In a Jupyter environment, 3D Slicer is accessible through the [SlicerJupyter](https://github.com/Slicer/SlicerJupyter) kernel and acts as a client for the MONAI Label server.

The MONAI Core, MONAI Label, and 3D Slicer (SlicerJupyter) come pre-installed with the JupyterLab `MONAI_ML` [feature option](/user/jupyter-notebooks.md#feature-options).

{% hint style="success" %}
For the full list of pre-installed packages, see the [JupyterLab in-product documentation](https://platform.dnanexus.com/app/app-dxjupyterlab).
{% endhint %}

## Using MONAI Core

For sample Jupyter notebooks and tutorials, see the official [project MONAI tutorials](https://github.com/Project-MONAI/tutorials).

You can find technical documentation for [MONAI Core](https://monai.readthedocs.io/en/stable/).

## Using MONAI Label with 3D Slicer

For examples showing how to use 3D Slicer with MONAI Label, see the following sample Jupyter notebooks in the DNAnexus OpenBio repository:

* [Radiology Auto-Segmentation and Training with MONAI Label and 3D Slicer (NIfTI/CT)](https://github.com/dnanexus/OpenBio/blob/master/monai/monailabel_3dslicer_radiology.ipynb): Shows auto-segmentation and model training on NIfTI CT spleen data using MONAI Label and 3D Slicer (SlicerJupyter).
* [Whole Brain Segmentation with MONAI Label and 3D Slicer (DICOM/MRI)](https://github.com/dnanexus/OpenBio/blob/master/monai/monailabel_3dslicer_monaibundle_DICOM.ipynb): Shows auto-segmentation and model training on DICOM MRI brain data, including DICOM-to-NIfTI conversion and interactive annotation in 3D Slicer.

For general examples and tutorials on using MONAI Label and 3D Slicer (SlicerJupyter), explore the following GitHub repositories:

* MONAI Label tutorials: [Project-MONAI/tutorials/monailabel](https://github.com/Project-MONAI/tutorials/tree/main/monailabel)
* 3D Slicer (SlicerJupyter) example notebooks: [Slicer/SlicerNotebooks](https://github.com/Slicer/SlicerNotebooks/)


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