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Study identifier: NCT04921020 Synced from ClinicalTrials.gov · July 29, 2026
● Recruiting

Assessment of Eyelid Topology and Kinetics Based on Deep Learning Method

Condition: Eyelid Diseases  ·  Sponsor: Second Affiliated Hospital, School of Medicine, Zhejiang University

PhaseN/A
Planned participants500
Who can joinAll sexes, N/A to no upper limit
Healthy volunteersYes

About this study

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.

This description comes directly from the study's public registry record.

Talk to the study team

Juan Ye  ·  +86-571-87783897  ·  yejuan@zju.edu.cn

Lixia Lou  ·  +86-15088681589  ·  loulixia110@zju.edu.cn

Always discuss trial participation with your own doctor first.

Locations (1)

Juan YeHangzhou, Zhejiang, ChinaRecruiting

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Source record: clinicaltrials.gov/study/NCT04921020