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
OUR MISSION
What is our
mission
Empowering medical data sharing while
protecting patients’ privacy
WHY US
Status Quo vs Glendor
Fully Automatic in Situ PHI De-identification of Medical Images,
Autonomous, Automatic, Seamless
Status Quo
Manual De-Identification
Manually de-identify medical images by blacking out names and other private info
- Non-scalable
- Time-consuming
- Requires trained technicians
Templates
For each group of similar images 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 originating hardware/software settings change
- Does not work with unknown images
3rd party cleansing
Unredacted images are 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
Flexible – works with not-seen-before images by
mimicking human behavior in anticipating variability
In Situ – Protected Health is sanitized on
customer premises/customer cloud and are not
shared with any 3rd party (including Glendor)
for de-identification
Burned-in and Metadata – Sanitizes both burned-in
pixel data and standard and private metatags
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
BEFORE
AFTER
In Situ
Original images are sanitized on customer's premises/customer's cloud
Autonomous
No Internet connection is required to run the software
Automatic
Does not require tuning, templates, or manual intervention
Pixels and Metadata
Sanitizes both pixel data and standard and private meta tags
Variety of Modalities
Works with X-rays, CT Scans, MRIs, Ultrasounds, OCTs, …
Variety of Formats
DICOM, JPEG, JPEG2000, E2E, …
Seamless
Designed to be easily incorporated as a node in an imaging workflow
ABOUT US
About Glendor
Glendor was founded by the specialists in the areas of Natural Language Processing, Machine Learning, Speech Recognition, OCR and Image Processing.
After three years of Research & Development, Glendor has developed PHI Sanitizer, an AI based system for automatic removal of PHI information from medical images and metadata.
Get in touch
