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Thanks for the question. If so, I suppose it's simple. We are making some E2E tutorials/Doc for MONAI Label+3D Slicer use cases. It's pending to merge. Especially this tutorial for Radiology app and use python script for config models/network. Inference pipeline till Section 2. And you can ignore section 3-4 for training and active learning. And MONAI Label is also supporting bundles, if you prefer to use You could only do inference step and ignore training, then after getting all annotated labels, you could train your data in many ways with local server. Thanks. |
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I have now returned back to MONAI Label for further testing, and we wanted to test it on a new application. Our goal is to be able to annotate locally through 3D Slicer, but train on a local server we control. The idea is basically to reduce the compute load on the local annotation machine by training on a server instead, which have access to a much larger GPU. We are annotating CT data.
Is that possible? If yes, are there any documentations on how to do that?
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