Remove PHI from Your Digital Pathology Data

As data sharing becomes essential for advancing digital pathology and AI-driven research, protecting patient privacy is more critical—and more complex—than ever. PHI and PII can exist in unexpected places within whole slide images, from embedded text on labels to metadata fields and scanner comments. Without proper anonymization, these details can limit collaboration, delay publication, and increase compliance risk.

In this webinar, Kitware’s experts will show how to identify and remove sensitive information from WSI data while maintaining traceability and data integrity. You’ll learn best practices for developing anonymization policies, validating that your images are PHI-free, and integrating automated workflows that scale across large datasets.

Attendees will also gain insight into Kitware’s ImageDePHI framework, which combines automation, transparency, and format flexibility to make de-identification faster and more reliable. Whether you’re preparing data for a publication, a multi-site study, or AI/ML model development, this session will equip you with the strategies and tools to protect patient privacy and streamline collaboration.

During this webinar, you will learn how to:

1. Recognize where PHI hides in pathology images.
2. Adopt practical strategies for de-identification at scale.
3. Validate that your data is truly PHI-free.
4. Develop adaptable anonymization policies for your projects.
5. Accelerate collaboration and publication readiness.