Reconstruction Technology to Auxiliary Diagnosis and Guarantee Patient Privacy

September 16, 2021 updated by: Haotian Lin, Sun Yat-sen University

Using a Reconstruction Technology With Facial Pathological Features to Auxiliary Diagnosis and Guarantee Patient Privacy

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.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Anticipated)

400

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • China
    • Guangdong
      • Guangzhou, Guangdong, China, 510000
        • Recruiting
        • Zhongshan Ophthalmic Center
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

Outpatients from strabismus departments, paediatric ophthalmology departments, TAO departments, and ophthalmic plastic departments.

Description

Inclusion Criteria:

  • The quality of facial images should be clinically acceptable.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
facial videos dataset
facial videos collected from Zhongshan Ophthalmic Center of Sun Yat-sen University.
Diagnostic test: DM
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

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Diagnostic consistency
Time Frame: baseline
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

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sun Yat-sen University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

May 10, 2020

Primary Completion (Anticipated)

September 20, 2021

Study Completion (Anticipated)

January 30, 2022

Study Registration Dates

First Submitted

September 16, 2021

First Submitted That Met QC Criteria

September 16, 2021

First Posted (Actual)

September 28, 2021

Study Record Updates

Last Update Posted (Actual)

September 28, 2021

Last Update Submitted That Met QC Criteria

September 16, 2021

Last Verified

September 1, 2021

More Information

Terms related to this study

Other Study ID Numbers

  • 2021KYPJ77

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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Locations

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