Reconstruction Technology to Auxiliary Diagnosis and Guarantee Patient Privacy
Using a Reconstruction Technology With Facial Pathological Features to Auxiliary Diagnosis and Guarantee Patient Privacy
1 other identifier
observational
400
1 country
1
Brief Summary
Medical data that contain facial images are particularly sensitive as they retain important personal biometric identity, privacy protection. We developed a novel technology called "Digital Mask" (DM), based on real-time three-dimensional (3D) reconstruction and deep learning algorithm, to extract disease-relevant features but remove patient identifiable features from facial images of patients.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started May 2020
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
May 10, 2020
CompletedFirst Submitted
Initial submission to the registry
September 16, 2021
CompletedPrimary Completion
Last participant's last visit for primary outcome
September 20, 2021
CompletedFirst Posted
Study publicly available on registry
September 28, 2021
CompletedStudy Completion
Last participant's last visit for all outcomes
January 30, 2022
CompletedSeptember 28, 2021
September 1, 2021
1.4 years
September 16, 2021
September 16, 2021
Conditions
Outcome Measures
Primary Outcomes (1)
Diagnostic consistency
For each eye, both the diagnosis from the original videos and the diagnosis from the DM-reconstructed videos were recorded and compared. If the two diagnoses were consistent, it suggests that the reconstruction would be precise enough in clinical practice.
baseline
Study Arms (1)
facial videos dataset
facial videos collected from Zhongshan Ophthalmic Center of Sun Yat-sen University.
Interventions
A new technology based on 3D reconstruction and deep learning algorithm to irreversibly erase the biometric attributes whilst retaining the clinical attributes needed for diagnosis and management
Eligibility Criteria
Outpatients from strabismus departments, paediatric ophthalmology departments, TAO departments, and ophthalmic plastic departments.
You may qualify if:
- The quality of facial images should be clinically acceptable.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Zhongshan Ophthalmic Center
Guangzhou, Guangdong, 510000, China
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Clinical Professor
Study Record Dates
First Submitted
September 16, 2021
First Posted
September 28, 2021
Study Start
May 10, 2020
Primary Completion
September 20, 2021
Study Completion
January 30, 2022
Last Updated
September 28, 2021
Record last verified: 2021-09