Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration.

ABSTRACT:

Purpose

To validate the performance of a commercially available, CE-certified deep learning (DL) system, RetCAD v.1.3.0 (Thirona, Nijmegen, The Netherlands), for the joint automatic detection of diabetic retinopathy (DR) and age-related macular degeneration (AMD) in colour fundus (CF) images on a dataset with mixed presence of eye diseases.

Methods

Evaluation of joint detection of referable DR and AMD was performed on a DR-AMD dataset with 600 images acquired during routine clinical practice, containing referable and non-referable cases of both diseases. Each image was graded for DR and AMD by an experienced ophthalmologist to establish the reference standard (RS), and by four independent observers for comparison with human performance. Validation was furtherly assessed on M

SUBMITTER: Gonzalez-Gonzalo C 

PROVIDER: S-EPMC7318689 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature