How to Get Started with MONAI Label: A Step-by-Step Guide

Sep 25, 2021 | Data Science

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In the world of medical imaging, efficient and precise image annotation is critical. Enter MONAI Label, an intelligent open-source tool designed to revolutionize the process of creating annotated datasets for clinical evaluation. This guide will lead you through the essentials of setting up and using MONAI Label to enhance your image labeling workflow.

Overview
Highlights and Features
Supported Matrix
Getting Started with MONAI Label
MONAI Label Tutorials
Additional Resources

Overview

MONAI Label streamlines the tedious task of medical image annotation, continuously improving through user interactions and data input. It bridges the gap between application developers and end-users, allowing clinicians and technologists to leverage the latest AI techniques effectively.

Highlights and Features

Framework for developing and deploying MONAI Label Apps.
Customizable labeling app design.
Annotation support through various third-party plugins.
Automated Active Learning workflow.

Getting Started with MONAI Label

To embark on your MONAI Label journey, follow these simple steps:

Step 1: Installation

To install MONAI Label, run:

pip install -U monailabel

For detailed installation instructions, please refer to the respective guides for Ubuntu and Windows.

Step 2: MONAI Label Sample Applications

You can choose from various sample applications in radiology, pathology, and video analysis. Explore options such as interactive segmentation, automated segmentation, or both.

Step 3: MONAI Label Supported Viewers

Integrate friendly viewers like 3D Slicer, OHIF, QuPath, and CVAT for a seamless experience. Configuration settings are available on their respective setup pages.

Step 4: Data Preparation

Prepare your data using either a local datastore or DICOMWeb support. For local data, ensure your folder structure adheres to the following format:

dataset/
  spleen_10.nii.gz
  spleen_11.nii.gz
  labels/
    final/
      spleen_10.nii.gz
      spleen_11.nii.gz

If using DICOMWeb, specify the service URL when starting the MONAI Label server.

Step 5: Start MONAI Label Server and Begin Annotating!

Once your setup is complete, launch the MONAI Label server using a sample app and dataset. Here’s a simple command to get you started:

monailabel start_server --app apps/radiology --studies datasets/Task09_Spleen/imagesTr --conf models segmentation

MONAI Label Tutorials

Dive deeper into MONAI Label with its comprehensive tutorials, covering various applications and workflows tailored for specific tasks.

Additional Resources

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Troubleshooting

If you encounter challenges during installation or usage:

Check compatibility with your operating system.
Ensure your GPU settings are correct if you’re using GPU acceleration.
Refer to the community channels for support.