Creating a Segmentation App Including Including Visualization with Clara-Viz

This tutorial shows how to create an organ segmentation application for a PyTorch model that has been trained with MONAI, and visualize the segmentation and input images with Clara Viz integration.

Setup

# Create a virtual environment with Python 3.7.
# Skip if you are already in a virtual environment.
# (JupyterLab dropped its support for Python 3.6 since 2021-12-23.
#  See https://github.com/jupyterlab/jupyterlab/pull/11740)
conda create -n monai python=3.7 pytorch torchvision jupyterlab cudatoolkit=11.1 -c pytorch -c conda-forge
conda activate monai

# Launch JupyterLab if you want to work on Jupyter Notebook
jupyter-lab

Executing from Jupyter Notebook

• Creating a Segmentation App Including Visualization with MONAI Deploy App SDK
  • Creating Operators and connecting them in Application class
    • Setup environment
    • Download/Extract ai_spleen_seg_data from Google Drive
    • Setup imports
    • Creating Model Specific Inference Operator classes
      • SpleenSegOperator
    • Creating Application class
  • Executing app locally
    • spleen_seg_operator.py
    • app.py
    • __main__.py
  • Packaging app

Download 03_segmentation_viz_app.ipynb

Creating a Segmentation App with MONAI Deploy App SDK Creating a Segmentation App Including Visualization with MONAI Deploy App SDK