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Assessment of Eyelid Topology and Kinetics Based on Deep Learning Method

NCT04921020 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 500

Last updated 2021-06-10

No results posted yet for this study

Summary

This study plans to assess eyelid topology (such as margin reflex distance, eyelid contour, and corneal exposure area) and blinking (such as frequency, velocity, and duration), using deep learning method to automatically extract eyelid topological features, and to predict subtypes of levator function, using deep learning method to extract blinking features, in order to provide new ideas and means to assess eyelid topology and kinetics.

Conditions

  • Eyelid Diseases

Interventions

OTHER

Photography

Facial photographs and blinking videos are taken

Sponsors & Collaborators

  • Second Affiliated Hospital, School of Medicine, Zhejiang University

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2020-08-01
Primary Completion
2025-08-01
Completion
2026-08-01

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04921020 on ClinicalTrials.gov