Zhejiang University

Juan Ye

Kai Jin

Xiaoyu Ma

Yaqi Wang

Yunxiang Li

Zhiyuan Gao

Disclosed is a fundus image quality evaluation method based on multi-source and multi-scale feature fusion, comprising following steps: S, acquiring multi-source fundus images, labeling the multi-source fundus images with four evaluation dimensions of brightness, blur, contrast and overall image quality, and forming training samples with the fundus image and labeling labels; S, constructing a fundus image quality evaluation network including a feature extraction module, a fusion module, an attention module and an evaluation module; S, training the fundus image quality evaluation network by using training samples to obtain a fundus image quality evaluation model; and S: inputting fundus images to be measured into the fundus image quality evaluation model, and outputting quality evaluation results through calculation. Also provided is a fundus image quality evaluation device based on above method.

Growing community of inventors

Hangzhou, China

Juan Ye