Abstract
Diabetic retinopathy is an eye disease that mainly affects the people having diabetes, and early identification is required to avoid vision loss. It can be done by trained ophthalmologist, but they are less in numbers; hence, computer-aided diagnosis system is used for automatic screening. In this paper, input image is taken from Indian Diabetic Retinopathy Image Dataset and histogram equalization; top-hat filters are used for enhancing retinal fundus images. Haralick features are extracted from the grayscaled image and filtered image and given to the feed forward neural network classifier. The accuracy obtained from the grayscaled image is 90%, and the accuracy obtained from filtered image is 95%.
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Asha Gnana Priya, H., Anitha, J. (2021). Identification of Diabetic Retinopathy for Retinal Images Using Feed Forward Neural Network. In: Khanna, A., Gupta, D., Pólkowski, Z., Bhattacharyya, S., Castillo, O. (eds) Data Analytics and Management. Lecture Notes on Data Engineering and Communications Technologies, vol 54. Springer, Singapore. https://doi.org/10.1007/978-981-15-8335-3_42
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DOI: https://doi.org/10.1007/978-981-15-8335-3_42
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