This repository hosts the notebooks for hosting a MONAI Bootcamp event. The data required for the notebooks are available through the download mechanisms given in each notebook or through the organizers.

You can find videos for our 2021 MONAI Bootcamp on the MONAI YouTube Channel. It partially covers some of the material below and shows how we ran the event.

Most of the notebooks in this repository would benefit considerably from having GPU support enabled. Therefore, it is recommended to run notebooks on Google Colab.

Intro to MONAI Core

(Requires Referral Code)

MONAI End-to-End Workflow

(Requires Referral Code)

MONAI Bundles and Model Zoo

(Requires Referral Code)

Creating a Simple Image Processing App with MONAI Deploy App SDK

Deploying a MedNIST Classifier App with MONAI Deploy App SDK

Creating a Segmentation App with MONAI Deploy App SDK

While using Google Colab, you cannot fully utilize Docker for packaging your MONAI Deploy Application Package (MAP). For this reason, we've commented out the docker-specific instructions within the notebooks so that there are no issues. These can be uncommented and run to demonstrate the packaging process if running locally.

MONAI Label requires a running server and an external viewing application, so we can't easily host a hands-on example using Google Colab. If you're interested in setting things up for MONAI Label locally, you can find the installation instructions in the installation section below.

You can find a video presentation + demo walkthrough by Andres Diaz-Pinto at the 2021 MONAI Bootcamp on YouTube here: https://www.youtube.com/watch?v=o8HipCgSZIw&list=PLtoSVSQ2XzyCobzE6NvwjNpITsQyPUtfs

To set up your local environment, you'll need to follow MONAI Core, MONAI Label, and MONAI Deploy installation instructions. Below you can find links to each projects installation documentation:

• MONAI Core Installation
• MONAI Label Installation
• MONAI Deploy Installation

If your local machine has GPU support, please follow the official PyTorch documentation on how to install PyTorch with GPU support in your local environment, depending on your system configuration.