Artificial Intelligence-Enabled Facial Privacy Protection for Ocular Diagnosis: Development and Validation Study.

ABSTRACT:

Background

Facial biometric data, while valuable for clinical applications, poses substantial privacy and security risks.

Objective

This paper aims to address the privacy and security concerns related to facial biometric data and support auxiliary diagnoses, in pursuit of which we developed Digital FaceDefender, an artificial intelligence-driven privacy safeguard solution.

Methods

We constructed a diverse set of digitally synthesized Asian face avatars representing both sexes, spanning ages 5 to 85 years in 10-year increments, using 70,000 facial images and 13,061 Asian face images. Landmark data were separately extracted from both patient and avatar images. Affine transformations ensured spatial alignment, followed by color correction and Gaussian blur to enhance fus

SUBMITTER: Tan H 

PROVIDER: S-EPMC12266301 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature