Artificial Intelligence System for Assessing Image Quality of Fundus Images and Its Effects on Diagnosis

Sun Yat-sen University

Status: Unknown

Conditions: Artificial Intelligence; Retinal Diseases

Treatments: Device: Taking a fundus image

Study type: Observational

Funder types: Other

Identifiers

NCT04289064

IMAQUA2020-China-01

Details and patient eligibility

About

Fundus images are widely used in ophthalmology for the detection of diabetic retinopathy, glaucoma and other diseases. In real-world practice, the quality of fundus images can be unacceptable, which can undermine diagnostic accuracy and efficiency. Here, the researchers established and validated an artificial intelligence system to achieve automatic quality assessment of fundus images upon capture. This system can also provide guidance to photographers according to the reasons for low quality.

Enrollment: 300 estimated patients

Sex: All

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Patients should be aware of the contents and signed for the informed consent.

Exclusion criteria

• 1. Patients who cannot cooperate with a photographer such as some paralytics, the patients with dementia and severe psychopaths.
• 2. Patients who do not agree to sign informed consent.

Trial design

300 participants in 1 patient group

Fundus image quality assessment

Description:

Device: an artificial intelligence system for quality assessment of fundus images. These patients are enrolled in primary healthcare units or the AI clinic at Zhongshan Ophthalmic Center.

Treatment:

Device: Taking a fundus image