Monai

Description

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.

Environment Modules

Run module spider monai to find out what environment modules are available for this application.

System Variables

HPC_MONAI_DIR - installation directory
HPC_MONAI_BIN - executable directory
HPC_MONAI_LIB - library directory

HPC_MONAILABEL_DIR - MONAI label installation directory

MONAI core

NGC container usage:

ml purge
ml ngc-monai/<version>
python <your__python_script>

MONAI label

NGC container usage:

Server:
- 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
3DSlicer client
- Start Open On Demand (OOD) session
- Start Console in hwgui with 1 GPU: gpu:geforce:1
- In console: load & start Slicer
  - ```
  ml qt/5.15.4 slicer/4.13.0
```
- ```
vglrun -d :0.$CUDA_VISIBLE_DEVICES 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!