Survey or Review on the Deep Learning Techniques for Retinal Image Segmentation in Predicting/Diagnosing Diabetic Retinopathy

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Author(s): Sowmiya R. (Puducherry Technological University, India)and Kalpana R. (Puducherry Technological University, India)
Copyright: 2022
Pages: 23
Source title: AI-Enabled Multiple-Criteria Decision-Making Approaches for Healthcare Management
Source Author(s)/Editor(s): Sandeep Kumar Kautish (Chandigarh University, Mohali, India)and Gaurav Dhiman (Government Bikram College of Commerce, India & Lebanese American University, Lebanon)
DOI: 10.4018/978-1-6684-4405-4.ch010

Keywords: Artificial Intelligence / Computer Science & IT / Medical Information Science Reference / Medical Technologies

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Abstract

Artificial intelligence (AI)-based image segmentation plays an important role in image processing and computer vision. AI can be used in the medical field (e.g., ophthalmology, disease prediction which involves direct visualization and imaging) as a frequent method for diagnosis. Deep learning comes under machine learning and as a part of AI. Deep learning algorithms have yielded considerable results in the medical field. Diabetic retinopathy is one of the most common causes of blindness, which is diagnosed by examining the appearance of the retina. The diabetic retinopathy stages are determined based on the changes seen in retina or retinal image. This chapter gives a detailed survey on different algorithms used for diagnosing diabetic retinopathy and different deep learning techniques used for medical image segmentation.

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Survey or Review on the Deep Learning Techniques for Retinal Image Segmentation in Predicting/Diagnosing Diabetic Retinopathy

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