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Construction, evaluation, and application of an automatic measurement model for eye parameters in ultrasound biomicroscopy images based on deep learning

Construction, evaluation, and application of an automatic measurement model for eye parameters in ultrasound biomicroscopy images based on deep learning

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500095826
Enrollment
Unknown
Registered
2025-01-14
Start date
2025-01-30
Completion date
Unknown
Last updated
2025-01-27

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

ametropia

Interventions

Trail group:no

Sponsors

Huangshi Aier Eye Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 50 Years

Inclusion criteria

Inclusion criteria: 1. The anterior and posterior surfaces of the cornea are clearly visible, (2) the iris pigment epithelium layer and the anterior surface of the lens are clearly visible in terms of reflection, (3) the anterior surface of the lens is tangent to the posterior surface of the iris, and (4) each image contains bilateral ACA.

Exclusion criteria

Exclusion criteria: 1.UBM images caused by motion artifacts, incomplete anterior segment, or related structural abnormalities;

Design outcomes

Primary

MeasureTime frame
anterior chamber depth;horizontal distance of sulcus to sulcus;—

Secondary

MeasureTime frame
pupil size;horizontal distance of anterior chamber angle to anterior chamber angle;—

Countries

China

Contacts

Public ContactWu Xiang

Huangshi Aier Eye Hospital

wuxiang@aierchina.com+86 714 3268374

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026