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Hypertensive Retinopathy Classification Using Improved Clustering Algorithm and the Improved Convolution Neural Network

Hypertensive Retinopathy Classification Using Improved Clustering Algorithm and the Improved Convolution Neural Network
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Author(s): Bhimavarapu Usharani (Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, India)
Copyright: 2022
Pages: 13
Source title: Deep Learning Applications for Cyber-Physical Systems
Source Author(s)/Editor(s): Monica R. Mundada (M.S. Ramaiah Institute of Technology, India), S. Seema (M.S. Ramaiah Institute of Technology, India), Srinivasa K.G. (National Institute of Technical Teachers Training and Research, Chandigarh, India) and M. Shilpa (M.S. Ramaiah Institute of Technology, India)
DOI: 10.4018/978-1-7998-8161-2.ch007

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Abstract

Hypertensive retinopathy is a disorder that causes hypertension which includes abnormalities in the retina that triggers vision problems. An effective automatic diagnosis and grading of the hypertensive retinopathy would be very useful in the health system. This chapter presents an improved activation function on the CNN by recognizing the lesions present in the retina and afterward surveying the influenced retina as indicated by the hypertensive retinopathy various sorts. The current approach identifies the symptoms associated of retinopathy for hypertension. This chapter presents an up-to-date review on hypertensive retinopathy detection systems that implement a variety of image processing techniques, including fuzzy image processing, along various improved activation function techniques used for feature extraction and classification. The chapter also highlights the available public databases, containing eye fundus images, which can be currently used in the hypertensive retinopathy research.

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