Integrating AI and Data Science in Digital Pathology

Integrating AI into digital pathology is a powerful but often complex task. Many teams face challenges when organizing pathology data for machine learning, deploying models in clinical or research environments, or scaling their workflows across computing platforms.

In this webinar, Kitware experts will demonstrate how HistomicsTK, our open-source platform for digital pathology, bridges these gaps—making it easier to manage data, apply custom AI models, and collaborate across teams. You’ll learn how to:

• Bring your own AI/ML models or integrate models from the MONAI zoo
• Maximize training performance with high-quality annotations
• Organize and manage large datasets with rich metadata
• Customize interfaces for specific pathology tasks
• Deploy solutions across laptops, cloud (AWS/GCP), and HPC environments

Whether you’re a pathologist, data scientist, or software developer, you’ll walk away with practical strategies and live demonstrations that show how to bring your models to your data—and put them to work effectively.

During this webinar, Kitware’s experts will:

1. Demonstrate how to integrate AI/ML models—including MONAI zoo and custom models—into HistomicsTK.
2. Highlight how data quality and comprehensive annotations improve model training.
3. Show how to customize pathology workflows with tools like Guided Labeling.
4. Present deployment strategies across local, cloud, and HPC systems.
5. Walk through real-world examples using actual pathology datasets.