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Research on Feature Extraction Method of Fundus Image Based on Deep Learning

机译：基于深度学习的眼底图像特征提取方法研究

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摘要

Image feature extraction is a key step in medical image processing, and it also plays an important role in the recognition and classification of medical images. A feature extraction method of fundus images using deep learning technology is proposed to recognize and classify fundus images. Firstly, the fundus image in the data set needs to be preprocessed. Then, the fundus image is extracted in the VGG16 network for the optic cup and disc region. Finally, the fundus feature image is input into the improved Softmax classifier for recognition and classification. The experimental results show that the fundus image feature extraction method used in the fundus images of glaucoma patients and normal people has a higher classification accuracy rate and the classification effect is better.
机译：图像特征提取是医学图像处理的关键步骤，它也在医学图像的识别和分类中起着重要作用。建议使用深层学习技术的眼底图像特征提取方法识别和分类眼底图像。首先，需要预处理数据集中的基底图像。然后，在用于光学杯和盘区域的VGG16网络中提取眼底图像。最后，基底特征图像被输入到改进的SoftMax分类器中，以进行识别和分类。实验结果表明，青光眼患者眼底图像和正常人的眼底图像特征提取方法具有更高的分类精度率，分类效果更好。

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