A new handheld fundus camera combined with visual artificial intelligence facilitates diabetic retinopathy screening.

ABSTRACT:

Aim

To explore the performance in diabetic retinopathy (DR) screening of artificial intelligence (AI) system by evaluating the image quality of a handheld Optomed Aurora fundus camera in comparison to traditional tabletop fundus cameras and the diagnostic accuracy of DR of the two modalities.

Methods

Overall, 630 eyes were included from three centers and screened by a handheld camera (Aurora, Optomed, Oulu, Finland) and a table-top camera. Image quality was graded by three masked and experienced ophthalmologists. The diagnostic accuracy of the handheld camera and AI system was evaluated in assessing DR lesions and referable DR.

Results

Under nonmydriasis status, the handheld fundus camera had better image quality in centration, clarity, and visible range (1.47, 1.48,

SUBMITTER: Ruan S 

PROVIDER: S-EPMC8995718 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature