3 Resources we released in the past 2 weeks for nnUNet

In the past 2 weeks we released a ton of information about how to nnUNet to build powerful medical imaging segmentation models. Here's a summary of them.
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1 - We released a 2-hours course on our Youtube channel.
This video will take you from zero to hero on how to start using nnUNet and train it on your own custom data.
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2 - We released a written guide on our website.
You can use this guide to quickly jump into the parts that interest you about how to use nnUNet.
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3 - We released a short video on how to integrate your trained nnUNet model directly into 3D Slicer.
You can use this guide to integrate your trained model as part of your workflow if you use 3D Slicer. One straightforward application of this is model-led annotation.
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X Post of the Day

Google introduces Explainable AI in Medical Imaging!

itinai.com @itinaicom "🔍 Google AI introduces StylEx, a new framework for explaining AI models in medical imaging. This groundbreaking approach generates counterfactual images and sheds light on classifier predictions. Dive into the research and evolve your company with #AI!… https://itinai.com/google-ai-proposes-a-machine-learning-framework-for-understanding-ai-models-in-medical-imaging/ 8:33 AM • Jun 9, 2024 0 Retweets 1 Likes

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TotalSegmentator Has a New Feature!

If you've been a subscriber for a long time then you've probably seen me cover TotalSegmentator multiple times! This is because, the folks behind it keep updating it with new awesome features every few weeks or months.

The latest feature?

TotalSegmentator now supports MR images!

It can segment 59 anatomical structures in MR images, regardless of sequence or contrast!

You can find out more about it in the official github repo and also in the original paper.

Btw, TotalSegmentator is based on nnUNet models! So if you plan to build AI models similar to what TotalSegmentator is doing, then the guides we shared above would be a great starting point for you!