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<!DOCTYPE html>
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<h2 class="mb-6 section-heading">MONAI Core</h2>
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<p class="py-2">MONAI Core is the flagship library of Project MONAI and provides domain-specific capabilities for training AI models for healthcare imaging. These capabilities include medical-specific image transforms, state-of-the-art transformer-based
3D Segmentation algorithms like UNETR, and an AutoML framework named DiNTS.</p>
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<p class="code p-4 bg-neutral-lightgray w-72">$ pip install monai</p>
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<p class="py-4 ">
MONAI Core is focused on bringing the state-of-the-art to the broader medical community. You can see some of these features below and start using them today through our tutorials.
</p>
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<h2 class="text-2xl font-bold pb-4">MedNIST Intro</h2>
<h3 class="text-lg font-bold pb-4 text-brand-primary">The Basics</h3>
<p class="pb-4">Learn how to use MONAI Transforms, Datasets, and Networks on MedNIST.</p>
<div class="text-brand-primary font-bold"><a href="https://github.com/Project-MONAI/tutorials/blob/main/2d_classification/mednist_tutorial.ipynb" target="_blank"> Learn More > </a></div>
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<h2 class="text-2xl font-bold pb-4">Low-Code Segmentation Framework</h2>
<h3 class="text-lg font-bold pb-4 text-brand-primary">Auto3DSeg</h3>
<p class="pb-4">A comprehensive solution for large-scale 3D medical image segmentation.</p>
<div class="text-brand-primary font-bold"><a href="https://github.com/Project-MONAI/tutorials/tree/main/auto3dseg" target="_blank"> Learn More > </a></div>
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<h2 class="text-2xl font-bold pb-4">Self-Supervised Learning</h2>
<h3 class="text-lg font-bold pb-4 text-brand-primary">Utilize Unlabeled Data</h3>
<p class="pb-4">Generate pre-trained weights using unlabeled data then use the pre-weights to fine-tune.</p>
<div class="text-brand-primary font-bold"><a href="https://github.com/Project-MONAI/tutorials/tree/main/self_supervised_pretraining" target="_blank"> Learn More > </a></div>
</div>
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<h2 class="text-2xl font-bold pb-4">Transformer-Based Nets</h2>
<h3 class="text-lg font-bold pb-4 text-brand-primary">UNETR / Swin UNETR</h3>
<p class="pb-4">The foundation of a new class of transformer-based models with hierarchical encoders.</p>
<div class="text-brand-primary font-bold"><a href="https://github.com/Project-MONAI/tutorials/blob/main/3d_segmentation/unetr_btcv_segmentation_3d.ipynb" target="_blank"> Learn More > </a></div>
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MONAI Core makes it easy to use only the functionality you need. By focusing on extending PyTorch classes, you can integrate most MONAI APIs directly in to your current workflow.
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<li><a href="https://docs.monai.io/en/stable/metrics.html" target="_blank">Metrics</a></li>
<li><a href="https://docs.monai.io/en/stable/losses.html" target="_blank">Losses</a></li>
<li><a href="https://docs.monai.io/en/stable/networks.html" target="_blank">Networks</a></li>
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<li><a href="https://docs.monai.io/en/stable/transforms.html" target="_blank">Transforms</a></li>
<li><a href="https://docs.monai.io/en/stable/optimizers.html" target="_blank">Optimizers</a></li>
<li><a href="https://docs.monai.io/en/stable/inferers.html" target="_blank">Inferers</a></li>
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<li><a href="https://docs.monai.io/en/stable/utils.html" target="_blank">Utils</a></li>
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<p class="font-bold text-xl mb-4 text-brand-primary">Install MONAI Core</p>
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Below are ways that you can start using, contributing, and interacting with other members of the MONAI Core community!
</p>
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<p class="text-3xl font-bold align-middle text-brand-primary">96+<br>Code<br>Contributors</p>
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<p class="pb-4">Start contributing to the MONAI Core repo by submiting a bug, requesting a feature, or starting a discussion today!</p>
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<p class="pb-4">Ready to get started using MONAI Core? You can find all of our documentation to help get you started or answer any of your questions!</p>
<div class="flex flex-wrap justify-center"><a class="brand-btn" href="https://docs.monai.io/en/stable/" target="_blank"> Deep Dive</a></div>
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