The MONAI framework is the open-source foundation being created by Project MONAI. MONAI is a freely available, community-supported, PyTorch-based framework for deep learning in healthcare imaging. It provides domain-optimized foundational capabilities for developing healthcare imaging training workflows in a native PyTorch paradigm.
Project MONAI also includes MONAI Label, an intelligent open source image labeling and learning tool that helps researchers and clinicians collaborate, create annotated datasets, and build AI models in a standardized MONAI paradigm.
module spider monai to find out what environment modules are available for this application.
- HPC_MONAI_DIR - installation directory
- HPC_MONAI_BIN - executable directory
- HPC_MONAI_LIB - library directory
- HPC_MONAILABEL_DIR - MONAI label installation directory
NGC container usage: ml purge ml ngc-monai/<version> python <your__python_script>
NGC container usage:
To start the server as a slurm job: ml purge ml ngc-monailabel/<version> sbatch start_monai_server_readonly.sh
Note server address from job output: used in next step
2) 3DSlicer client
- Start Open On Demand (OOD) session - Start Console in hwgui with 1 GPU: gpu:geforce:1 - In console: load & start Slicer ml slicer/4.13.0 Slicer - In Slicer GUI: Select module: Active Learning -> MONAILabel Fill in server address, e.g.: http://c1007a-s17:8000/ Click on refresh button next to server address Load Next Sample You are good to go! Enjoy!
MONAI on HiPerGator Tutorial Recordings and Slides
- Recording: MONAI Label for Medical Imaging and slides: File:2022-Feb-MONAILabel-Tutorial-UF.pdf, by Dr. Huiwen Ju, Feb. 22, 2022
MONAI 3-day Bootcamp Recordings and Learning Materials
MONAI Deploy App SDK
If you would like to install MONAI on your own platforms, here are some useful links:
MONAI Core tutorials