You can ask MONAILabel developers to help you port the old model into a MONAILabel app.
2 Likes
Thanks for the ping, @lassoan
@Pari_TF, have you considered using MONAI Label (GitHub - Project-MONAI/MONAILabel: MONAI Label is an intelligent open source image labeling and learning tool.)?
It is easy to get a pretrained model for lung segmentation using MONAI Label. Are you using a public dataset?
1 Like
Thanks for your reply. No, I haven’t used MONAI Label. That’s great. I will try it. Thank you so much. Yes, I’m working on a public dataset.
1 Like
I am using my own data to segment lung nodules. The training set has been using the annotation_lung_tumor model of Nvidia AIAA. Now that the test set is ready, I found that the above model is no longer available, which caused me a lot of trouble. Can you help me add the old model to MONAI Label, thanks.
Do you know which dataset they used to get that pretrained model? I think it is Task06_Lung (MSD - Google Drive) from the Medical Segmentation Decathlon but I’m not sure.
If that’s the dataset, you should be able to get a pretrained model fairly easy. Do you have a GPU-based PC?
It is indeed a model pre-trained with the Task06_Lung dataset, and we use boundary-point based segmentation of lung tumor on CT (AIAA for 3D Slicer). But now the model is not found in NVIDIA. Also, we have GPU-based PC.
1 Like
I was going to try this out but I am consistently running into
monailabel apps --download --name deepedit --output apps
Using PYTHONPATH=/home/rbumm:
App deepedit => /usr/monailabel/sample-apps/deepedit not exists
after a
pip install monailabel
This is with and w/o an elevated bash on Windows 10 Ubuntu WSL. Any ideas?
1 Like
@rbumm there were recently some changes in folder structure. Please try out the monailabel-weekly instead (pip install monailabel-weekly)
Then download the radiology app as follows:
monailabel apps --download --name radiology --output apps
As an example you could download and use the spleen dataset:
monailabel datasets --download --name Task09_Spleen --output datasets
Then start the server using the Deepedit model:
monailabel start_server --app apps/radiology --studies datasets/Task09_Spleen/imagesTr --conf models deepedit
Here you can see more details: GitHub - Project-MONAI/MONAILabel: MONAI Label is an intelligent open source image labeling and learning tool.
1 Like
Thanks, Andres, tried this already - pip uninstalled monailabel and pip installed monailabel-weekly, but there is a similar message:
monailabel apps --download --name radiology --output apps
Using PYTHONPATH=/home/rbumm:
App radiology => /usr/monailabel/sample-apps/radiology not exists
Probably a permission problem.
1 Like
This is strange 
Probably the weekly installation wasn’t clean. Please do a clean installation using a clean Python virtual environment.
Needed to install monailabel via github to make this working in Windows 10 WSL (see here).
1 Like
Hi @rbumm,
My bad, I just realised the weekly version doesn’t install the candidate release 0.4.0 
In order to use the radiology app you should either use directly the GitHub repo as you did or install directly the candidate release:
pip install monailabel==0.4.0rc3
Please let me know how that goes. Happy to help.
Andres
Hi!
I would like to use NVidia AIAA in 3d Slicer on my work (hospital) computer.
I get the error
Failed to fetch models from remote server. Make sure server address is correct and <server_uri>/v1/models is accessible in browser
I cannot access http://perklabseg.asuscomm.com:5000/v1/models from my browser.
I am probably behind a proxy. How I can configure the settings, so the AIAA would work?
Thanks!
Bor
Hello, I entered the URL http://perklabseg.asuscomm.com:5000/v1/models, but it shows that perklabseg.asuscomm.com is currently unable to handle this request. HTTP ERROR 502. What should I do? I can’t connect to the default server. Please help me.
This is a quickly evolving field. We don’t provide the NVIDIA AIAA demo server anymore, as the developers of this segmentation tool moved on to new technologies.
You can now use tools such as MONAIAuto3DSeg and TotalSegmentator extensions for simple server-less running of pre-trained models and MONAILabel for training your own models.
@lassoan Is it time to archive Nvidia AIAA from the Slicer extensions index? Otherwise it is likely a “tier 5” extension as it is not under active development with little to no support. This will help the community better understand what are the higher quality AI based extensions to use in Slicer.
I agree, making it a low-tier extension (when the tier system is introduced) is a good idea.