Abstract
Diabetic Macular Edema (DME) and Age-related Macular Degeneration (AMD) are the main causes of vision loss in patients with retinal diseases. Computer-assisted, deep learning-based enables intelligent analysis of the layered structure of the retina, which promotes intelligent medical reform. In this paper, we proposed an OCC-DME algorithm to adaptively identify the types of retinal diseases based on OCT image analysis and detection. After preprocessing, the lesions features of pucker in the retinal macular area can be extracted, and then update the weights of features and further to calculate through back propagation. Experimental analysis shows that our algorithm has a good classification accuracy rate and high recognition rate.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (No. 61701104), and by the Science and Technology Development Plan of Jilin Province, China (No.20200403039SF).
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Wang, L., Xie, W.C., Li, T., Liu, Y.M., Zhou, T.H. (2021). Retina Macular Edema and Age-Related Macular Degeneration Feature Recognition Method Based on the OCT Images. In: Pan, JS., Li, J., Namsrai, OE., Meng, Z., Savić, M. (eds) Advances in Intelligent Information Hiding and Multimedia Signal Processing. Smart Innovation, Systems and Technologies, vol 211. Springer, Singapore. https://doi.org/10.1007/978-981-33-6420-2_23
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DOI: https://doi.org/10.1007/978-981-33-6420-2_23
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