Implementation of Deep Learning Neural Network for Retinal Images

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Author(s): R. Murugan (National Institute of Technology Silchar, India)
Copyright: 2023
Pages: 19
Source title: Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-7544-7.ch039

Keywords: Knowledge Management and Library Science / Medical Diagnosis and Practice / Medical Imaging / Medical Information Science Reference

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Abstract

The retinal parts segmentation has been recognized as a key component in both ophthalmological and cardiovascular sickness analysis. The parts of retinal pictures, vessels, optic disc, and macula segmentations, will add to the indicative outcome. In any case, the manual segmentation of retinal parts is tedious and dreary work, and it additionally requires proficient aptitudes. This chapter proposes a supervised method to segment blood vessel utilizing deep learning methods. All the more explicitly, the proposed part has connected the completely convolutional network, which is normally used to perform semantic segmentation undertaking with exchange learning. The convolutional neural system has turned out to be an amazing asset for a few computer vision assignments. As of late, restorative picture investigation bunches over the world are rapidly entering this field and applying convolutional neural systems and other deep learning philosophies to a wide assortment of uses, and uncommon outcomes are rising constantly.

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Implementation of Deep Learning Neural Network for Retinal Images

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