An observational study in Eyelid Diseases, sponsored by Second Affiliated Hospital, School of Medicine, Zhejiang University. Recruiting at 1 site in China. Per ClinicalTrials.gov, last updated 2021-06-10.
Sponsored by Second Affiliated Hospital, School of Medicine, Zhejiang University · Observational
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.
100 normal volunteers without eyelid diseases 100 patients with blepharoptosis 100 patients with blepharospasm 100 patients with dry eye disease 100 patients with Graves' disease
Exclusion Criteria:
variable ptosis (e.g., myasthenia gravis), entropion, ectropion, enophthalmos, exophthalmos, strabismus, and abnormalities of pupil
Other: Photography
Other: Photography
Other: Photography
Other: Photography
Other: Photography
Facial photographs and blinking videos are taken
one-dimensional parameters of eyelid topology
Palpebral fissure length \[Margin reflex distance 1, Margin reflex distance 2\], Lid length \[Upper lid length, Lower lid length\], Multiple mid-pupil lid distances
Time frame: through study completion, 5 years
two-dimensional parameters of eyelid topology
Palpebral fissure area \[Medial area, Corneal area, Lateral area\]
Time frame: through study completion, 5 years
subtypes of levator function
Levator function is classified into three categories: good, fair and poor
Time frame: through study completion, 5 years
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Second Affiliated Hospital, School of Medicine, Zhejiang University