Thanks for the ping @rbumm
This is a very good question @S_Arbabi. At the moment, it is not straightforward to use nnUNET models in MONAI Label. However, for any model you have trained using nnUNET you could do the same using MONAI Label.
As an example of this, we’ve trained a whole-body CT segmentation model using the Total Segmentator dataset: model-zoo/models/wholeBody_ct_segmentation at dev · Project-MONAI/model-zoo · GitHub
Here is the video where I briefly talk about the technical details of this implementation:
I used a single SegResNet network and get comparable results. If needed, you could also implement multiple networks and do ensembling as done in the nnUNET framework.
Here you can see how the dataset should be prepared to use MONAI Label: MONAI Label Workshop - Project Week 38 - YouTube
I’d recommend you start with the segmentation model available on the latest MONAI Label version: MONAILabel/sample-apps/radiology at main · Project-MONAI/MONAILabel · GitHub
Update these label names according to your task:MONAILabel/segmentation.py at main · Project-MONAI/MONAILabel · GitHub
and put this to false so you start from scratch the training process: MONAILabel/segmentation.py at main · Project-MONAI/MONAILabel · GitHub
Hope this helps,