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Title
Deep convolutional neural network for the prognosis of diabetic retinopathy / A. Shanthini, Gunasekaran Manogaran, G. Vadivu
ISBN
9789811938771 (electronic bk.)
9811938776 (electronic bk.)
9789811938764 (print)
9811938768
Publication Details
Singapore : Springer, [2023]
Language
English
Description
1 online resource (80 pages)
Item Number
10.1007/978-981-19-3877-1 doi
Call Number
RE661.D5
Dewey Decimal Classification
617.7/35
Summary
This book discusses a detailed overview of diabetic retinopathy, symptoms, causes, and screening methodologies. Using a deep convolution neural network and visualizations techniques, this work develops a prognosis system used to automatically detect the diabetic retinopathy disease from captured retina images and help improve the prediction rate of diagnosis. This book gives the readers an understanding of the diabetic retinopathy disease and recognition process that helps to improve the clinical analysis efficiency. It caters to general ophthalmologists and optometrists, diabetologists, and internists who encounter diabetic patients and most prevalent retinal diseases daily.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed September 2, 2022).
Series
Series in bioengineering.
Introduction
Chapter 1
Background of diabetic retinopathy
Chapter 2
Classification of diabetic retinopathy
Chapter 3
Deep convolutional neural network architecture
Chapter 4
Deep convolutional neural network applications and visualization tools
Chapter 5
Multi-platform deployment for prognosis system
Chapter 6
Case Studies for diabetic retinopathy with a deep learning system.