Artificial Intelligence System for Assessing Image Quality of Slit-Lamp Images and Its Effects on Diagnosis

Sun Yat-sen University

Status: Unknown

Conditions: Artificial Intelligence; Anterior Segment Disorders

Treatments: Device: Taking slit-lamp images

Study type: Observational

Funder types: Other

Identifiers

NCT04314180

IMAQUA2020-China-02

Details and patient eligibility

About

Slit-lamp images are widely used in ophthalmology for the detection of cataract, keratopathy and other anterior segment disorders. In real-world practice, the quality of slit-lamp 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 slit-lamp 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

Slit-lamp image quality assessment

Description:

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

Treatment:

Device: Taking slit-lamp images