Overview
- Outlines a detailed overview of diabetic retinopathy, symptoms, causes and screening methodologies
- Presents a deep learning approach to automatically detect diabetic retinopathy from captured retina image
- Demonstrates a higher prediction rate of diabetic retinopathy and efficiency in early detection
Part of the book series: Series in BioEngineering (SERBIOENG)
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About this book
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.
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Table of contents (7 chapters)
Authors and Affiliations
About the authors
Dr. Gunasekaran Manogaran is currently working as Big Data Scientist at University of California, Davis, USA. He is also Adjunct Assistant Professor, Department of Computer Science and Information Engineering, Asia University, Taiwan, and Adjunct Faculty, in School of Computing, SRM Institute of Science and Technology, Kattankulathur, India. He is Visiting Researcher/Scientist at the University of La Frontera, Colombia, and the International University of La Rioja, Spain. He received his Ph.D. from the Vellore Institute of Technology University, India. He received his Bachelor of Engineering and Master of Technology from Anna University, India, and Vellore Institute of Technology University, India, respectively. He is author/co-author of more than 100 papers in conferences, book chapters, and journals, including IEEE Transactions on Industrial Informatics, IEEE Transactions on Computational Social Systems, IEEE Internet of Things, IEEE Intelligent System, IEEE Access, ACM Transactions on Multimedia Computing, Communications, and Applications.
Dr. G. Vadivu is working in the teaching profession for more than two decades. Currently, she is designated Professor and Program Coordinator in the Department of Data Science and Business Systems at SRM Institute of Science and Technology, Kattankulathur Campus, India. Her research areas include big data analytics, semantic web, data mining, and database systems. She published more than 30 research articles in a reputed journal listed in SCIE and Scopus. She has organized UGC sponsored workshop on .NET Technologies during 2006 and 2009. She received the Best Teaching Faculty Award and Certificate of Appreciation for the journal published in the year 2012. Also, she has completed Oracle Certification, Certification in Database Administration-Microsoft Technology Association, High-Impact Teaching Skills Certified by Dale Carnegie, and IBM-DB2 certification.
Bibliographic Information
Book Title: Deep Convolutional Neural Network for The Prognosis of Diabetic Retinopathy
Authors: A. Shanthini, Gunasekaran Manogaran, G. Vadivu
Series Title: Series in BioEngineering
DOI: https://doi.org/10.1007/978-981-19-3877-1
Publisher: Springer Singapore
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023
Hardcover ISBN: 978-981-19-3876-4Published: 25 August 2022
Softcover ISBN: 978-981-19-3879-5Published: 26 August 2023
eBook ISBN: 978-981-19-3877-1Published: 23 August 2022
Series ISSN: 2196-8861
Series E-ISSN: 2196-887X
Edition Number: 1
Number of Pages: IX, 75
Number of Illustrations: 12 b/w illustrations, 29 illustrations in colour
Topics: Biomedical Engineering and Bioengineering, Ophthalmology, Signal, Image and Speech Processing, Computational Intelligence