Glendor PHI Sanitizer
Do you need to share multimodal medical data? Are you confident in the effectiveness of your current de-identification process? Join us for a live demo to see how easy-to-integrate fully automatic Glendor PHI Sanitizer software can enhance your existing procedures.
Fully Automatic at Source Software for PHI De-identification of Multimodal Medical Data (Medical Images, Pathology, Reports, Videos, Photos, Audio)
USE CASES
Use Case 1: Data Leaving Customer's Network
Use Case 2: Data Entering Customer's Network
WHY US
Status Quo vs Glendor
Fully Automatic in Situ PHI De-identification of Multimodal Medical Data
Autonomous, Automatic, Seamless
Status Quo
Manual De-Identification
Manually de-identify medical data by blacking out names and other private info
- Non-scalable
- Time-consuming
- Requires trained technicians
Templates
For each group of similar images/documents/… specify regions containing private info to be blacked out
- Rigid and fragile
- Breaks on any deviation from the template
- Requires a new template every time data originating hardware/software settings change
- Does not work with unknown medical data
3rd party cleansing
Unredacted medical data is sent off-site for processing. Google Cloud Healthcare API Services, Amazon Rekognition Services and semi-automatic de-identification services
- Exposure
- Unredacted images leave the premises
- Unredacted images are shared with a third party
Glendor
PHI Sanitizer
Automatic
Does not require tuning, templates or manual intervention
At Source
Medical data is sanitized on customer premises/customer cloud and are not shared with any 3rd party (including Glendor) for de-identification
Easy to Integrate and Use
No BAA required, 1 min to install and start running. Designed to be integrated as a node into existing data workflows or to be used as a standalone tool
Multiple Modality Multiple Formats
Medical images, reports, pathology, videos, photos, audio
PRODUCTS
Glendor PHI Sanitizer
FULLY Automatic IN SITU Redaction of Protected Health Information from Medical Images (Pixels and Metadata), videos, photos, voice recordings and other medical data
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ABOUT US
About Glendor
We at Glendor are on a quest to safeguard patients’ privacy by de-identifying Protected Health Information (PHI) automatically and at source. Glendor was founded 7 years ago by specialists in the areas of Natural Language Processing, Machine Learning, Speech Recognition, OCR and Image Processing. With our Glendor PHI Sanitizer software one can easily prepare multimodal medical data for sharing and aggregation, while advancing clinical research and AI in medicine.
Latest News and Publications by the Team
EMERGE INNOVATION EXPERIENCE COMPETITION at HIMSS2025
🎉 Glendor is honored to be part of the Winner’s Circle in the Emerge Innovation Experience Contest at #HIMSS25. Category – Payer – Improving data & analytics capabilities and reach
HIMSS2025
Glendor is HIMSS 2025 Exhibitor, booth Caesar's Forum — C3102-14
Industry Perceptions Survey on AI Adoption and Return on Investment
Mitchell Goldburgh, Michael LaChance, Julia Komissarchik, Julia Patriarche, Joe Chapa, Oliver Chen, Priya Deshpande, Matthew Geeslin, Nina Kottler, Jennifer Sommer, Marcus Ayers & Vedrana Vujic 2023 Industry Perceptions Survey on AI Adoption and Return on Investment. Journal of Digital Imaging. Inform. med. (2024). https://doi.org/10.1007/s10278-024-01147-1
Challenges of Sensitive Images: A HIMSS-SIIM Enterprise Imaging Community Whitepaper
Alexander J. Towbin, Delaney D. Ding, Moneif Eid, Heather Kimball, Julia Komissarchik, John Memarian & Seetharam C. Chadalavada Special Challenges of Sensitive Images: A HIMSS-SIIM Enterprise Imaging Community Whitepaper, Journal of Digital Imaging. Inform. med. 37, 915–921 (2024). https://doi.org/10.1007/s10278-024-00980-8
Glendor PHI Sanitizer for Medical Images
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