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Research of Automated Maculopathy Screening Based on Deep Learning Techniques Using Optical Coherent Tomography Images

Research of Automated Maculopathy Screening Based on Deep Learning Techniques Using Optical Coherent Tomography Images

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR1800014389
Enrollment
Unknown
Registered
2018-01-10
Start date
2017-08-01
Completion date
Unknown
Last updated
2018-01-15

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

Conditions

Maculopathy

Interventions

Gold Standard:Clinical outcomes, retinal imaging examinations including OCT, fundus photography and fundus fluorescein angiography
Learning&#32
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Sponsors

The First Affiliated Hospital of Nanjing Medical University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: All patients who have visited ophthalmology clinics in the First Affiliated Hospital of Nanjing Medical University in recent 5 years and have done retinal imaging examinations for their routine clinical diagnosis and treatment, including OCT, fundus photography and fundus fluorescein angiography (at least have done OCT examinations) will be included in this study.

Exclusion criteria

Exclusion criteria: 1.Images without raw data, such as OCT images in paper versions provided by patients who did examinations in other hospitals. 2.Eyes with unclera refractive media, poor image signal or incompletely scanned OCT images; 3.Eyes filled with silicone oil or gas; 4.Patients who refuse to provide medical information or refuse to participate in clinical researchs.

Design outcomes

Primary

MeasureTime frame
SPE, SEN, ACC;

Contacts

Public ContactLiu Qinghuai

The First Affiliated Hospital of Nanjing Medical University

liuqh@njmu.edu.cn+86 13901585755

Outcome results

None listed

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