An Artificial-Intelligence-Based Automated Grading and Lesions Segmentation System for Myopic Maculopathy Based on Color Fundus Photographs.

ABSTRACT:

Purpose

To develop deep learning models based on color fundus photographs that can automatically grade myopic maculopathy, diagnose pathologic myopia, and identify and segment myopia-related lesions.

Methods

Photographs were graded and annotated by four ophthalmologists and were then divided into a high-consistency subgroup or a low-consistency subgroup according to the consistency between the results of the graders. ResNet-50 network was used to develop the classification model, and DeepLabv3+ network was used to develop the segmentation model for lesion identification. The two models were then combined to develop the classification-and-segmentation-based co-decision model.

Results

This study included 1395 color fundus photographs from 895 patients. The grading accur

SUBMITTER: Tang J 

PROVIDER: S-EPMC9206390 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature