Difference between revisions of "Monai"

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* HPC_{{uc:{{#var:app}}}}LABEL_DIR - MONAI label installation directory
 
* HPC_{{uc:{{#var:app}}}}LABEL_DIR - MONAI label installation directory
  
==MONAI core==
+
==More Information==
NGC container usage:
+
For quick guides on usage for MONAI Core/MONAI Label, visit [[Monai 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:
 
#**<pre>ml purge</pre>
 
#**<pre>ml ngc-monailabel/<version></pre>
 
#**<pre>sbatch start_monai_server_readonly.sh</pre>
 
#*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
 
#**<pre>ml qt/5.15.4 slicer/4.13.0</pre>
 
#**<pre>vglrun -d :0.$CUDA_VISIBLE_DEVICES Slicer</pre>
 
#*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!
 
==Learning Materials==
 
 
 
 
=== MONAI on HiPerGator Tutorial Recordings and Slides ===
 
=== MONAI on HiPerGator Tutorial Recordings and Slides ===
 
* Recording: [https://ufl.zoom.us/rec/play/2O1PqqMU7DJ2mexyn_Jfki3IGGcu3KjLV8iZ2dcT2Wztxx27dIO8g7W_nlWfEnKmoXASRFNBm7ihGWZU.n-AJRZLetesP4X9v?startTime=1658851332000 MONAI Label for Medical Imaging] and slides: [https://github.com/hw-ju/monai_uf_tutorials/blob/main/slides/MONAICore_tutorial_UF_July_2022.pdf MONAICore_tutorial_UF_July_2022.pdf]
 
* Recording: [https://ufl.zoom.us/rec/play/2O1PqqMU7DJ2mexyn_Jfki3IGGcu3KjLV8iZ2dcT2Wztxx27dIO8g7W_nlWfEnKmoXASRFNBm7ihGWZU.n-AJRZLetesP4X9v?startTime=1658851332000 MONAI Label for Medical Imaging] and slides: [https://github.com/hw-ju/monai_uf_tutorials/blob/main/slides/MONAICore_tutorial_UF_July_2022.pdf MONAICore_tutorial_UF_July_2022.pdf]

Revision as of 17:46, 5 May 2023

Description

monai website  

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

More Information

For quick guides on usage for MONAI Core/MONAI Label, visit Monai Usage.

MONAI on HiPerGator Tutorial Recordings and Slides

MONAI 3-day Bootcamp Recordings and Learning Materials

MONAI Deploy App SDK

MONAI Packages

If you would like to install MONAI on your own platforms, here are some useful links:

MONAI Core tutorials