Right now, there are some seriously powerful libraries and frameworks out there dedicated to medical imaging. They make the whole process of training and testing models so much easier for developers. Here is a quick breakdown of these libraries.

Nvidia’s Clara Medical#

Developed by Nvidia, Clara Medical is an awesome collection of powerful models for various tasks—like generating CT and MRI scans, as well as other challenges in this field, such as 3D medical image segmentation. Nvidia has also implemented various models here, like NV-Reason-CXR, which uses a VLM architecture to analyze and evaluate 3D images. It is truly one of a kind.

MONAI#

The MONAI (Medical Open Network for Artificial Intelligence) framework, developed in collaboration with Nvidia, is easily one of the most powerful tools in this space. Since it is built on top of PyTorch, working with it feels exactly like running a native PyTorch project. It gives you a ton of built-in utilities tailored for the medical field—ranging from data labeling with MONAI Label to deploying your models using MONAI Deploy. On top of that, it provides plenty of Foundation Models that you can easily fine-tune for your own research or projects. A great example is MAISI, which is a synthetic data generator for CT scans. You can use its features for a wide variety of tasks, like 2D and 3D segmentation using SwinUNETR, which comes pre-trained on CT scan images.

TorchXRayVision#

If you are working with Chest X-rays, this is a fantastic collection of datasets and models just for you. You can easily find highly robust pre-trained models for tasks like segmentation, classification, and more.

ANTsPyNet#

This one is a powerful suite of pre-trained models and popular architectures for training image processing models. It hooks you up with great architectures like U-Net and DenseNet for both 2D and 3D images, alongside a massive collection of models pre-trained on various datasets like Brain and Lung scans.

PathML#

A powerful library specifically built for handling Pathology images. It helps you out through different stages of your workflow, including data augmentation, model training, and building custom pipelines in this domain.

FastPathology#

An open-source software that packs a punch when it comes to running inference on pathology models. It offers great visualization features for the outputs of classification, object detection, and other models tailored for pathology images.