Classification and detection method for diabetic retinopathy based on the combination of improved Retinex image enhancement and deep learning
10.3969/j.issn.1005-202X.2024.09.005
- VernacularTitle:融合改进Retinex图像增强与深度学习的糖尿病视网膜分类检测方法
- Author:
Wenjing WANG
1
;
Lichuan ZHANG
;
Xin WANG
;
Yuhong LIU
Author Information
1. 成都医学院生物医学工程教研室,四川成都 610500
- Keywords:
deep learning;
image classification;
image enhancement;
diabetic retinopathy
- From:
Chinese Journal of Medical Physics
2024;41(9):1086-1092
- CountryChina
- Language:Chinese
-
Abstract:
Objective To present a novel method based on the image enhancement algorithm and deep learning for automatically classifying diabetic retinopathy images,and realizing the graded classification of fundus lesions.Methods An improved Retinex image enhancement algorithm was employed to preprocess the original images for significantly improving image quality and visual effect,and enhancing image clarity and contrast.Then,deep learning method was used to automatically detect and classify the degree of lesions in different periods.Results The proposed method was advantageous in improving classification accuracy,sensitivity,and specificity which were 5.4%,7.4%,and 16.6%higher than those of traditional Retinex method.Conclusion The proposed method can effectively realize the automatic detection and classification of diabetic retinopathy,which is helpful to enhance diagnostic accuracy and efficiency.
