Intended to foster understanding and awareness of anonymization challenges and use cases that have increased with the growth of AI
Laurel Bridge Software, a provider of imaging software solutions that enable health systems to orchestrate their medical imaging workflows, announces new educational materials on medical imaging anonymization. They are intended to educate healthcare providers and AI algorithm developers about the challenges of anonymizing medical imaging exams for AI/machine learning, research, and education. All were developed through a collaboration with Herman Oosterwijk, long-time educator, and consultant in medical imaging informatics, PACS, DICOM and HL7. Two new educational white papers and a video are available on the Laurel Bridge website.
White Paper, part one: Anonymization of Patient Information in Medical Imaging; State-of-the-Art and Challenges
White Paper, part two: Anonymization of Patient Information in Medical Imaging; State-of-the-Art and Challenges
Video: Medical Imaging Anonymization Challenges and Insights: Perspectives from Herman Oosterwijk
Digital medical images require anonymization of Protected Health Information in the DICOM header and in “burned-in” text. One might wonder why we are still struggling with anonymization after so many years of experience. The answer is that it is complicated!
Anonymization of medical images has been a challenge ever since digital medical imaging was introduced”, says Herman Oosterwijk, President of OTech. “When it was film-based, de-identifying an image was easy: One would simply cut off the corner of the film that included the patient information, or when making a duplicate, one would cover the patient information or obscure it with a black marker.”
Laurel Bridge has been helping healthcare providers and clinical trial investigators to support clinical workflows by anonymizing medical imaging studies as an extension of clinical reading workflows. In addition, Laurel Bridge is helping AI algorithm researchers and developers to anonymize very large medical imaging data sets that are used for training AI algorithms and for educational purposes.
“We have a number of OEM partners who have sought our help to anonymize patient data as part of their AI algorithm workflow”, says Jeff Blair, President of Laurel Bridge Software. “In addition, we have seen a significant increase in the number of healthcare providers and AI developers asking for assistance with their data anonymization and workflow needs. When Herman approached us and confirmed this trend, we realized some education was needed.”
The Laurel Bridge CompassTM – Routing Workflow Manager can automatically de-identify and re-identify medical images as part of clinical image routing workflows and in accordance with the DICOM Part 15 Standard. In addition, the Laurel Bridge AI Workflow Suite can facilitate the exchange of anonymized and re-identified patient information with AI algorithms, along with the fetching and routing of relevant prior exams that might be required to integrate algorithms into research and clinical workflows.
About Laurel Bridge Software
For over 20 years, Laurel Bridge Software has been providing healthcare organizations with enterprise imaging workflow solutions for image routing, prior exam fetching, migration, and modality worklist management. Our suite of highly configurable solutions solves complex, mission-critical imaging workflows that unify multiple business entities and their disparate clinical imaging systems. Laurel Bridge solutions reliably ensure that new and historical DICOM imaging studies, HL7 messages, and non-DICOM objects are available to the clinical staff, at the point-of-care. These imaging workflow solutions are implemented at thousands of healthcare providers, OEMs, teleradiology firms, radiology group practices, and AI algorithm companies, in more than 35 countries, directly and through integration partners. Learn more by visiting www.LaurelBridge.com.
