Skip to main content

Deep Convolutional Neural Network for The Prognosis of Diabetic Retinopathy

  • Book
  • © 2023

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)

This is a preview of subscription content, log in via an institution to check access.

Access this book

eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

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.

Similar content being viewed by others

Keywords

Table of contents (7 chapters)

Authors and Affiliations

  • Department of Data Science and Business Systems, SRM Institute of Science and Technology, Chennai, India

    A. Shanthini, G. Vadivu

  • University of California, Davis, USA

    Gunasekaran Manogaran

About the authors

Dr. A. Shanthini is currently working as Associate Professor in the Department of Data science and Business systems, SRM Institute of Science and Technology, Kattankulathur Campus, India. She received her Bachelor of Engineering, Master of Engineering and Ph.D. from Annamalai University, India. Her current research interests include Data analyticssh, machine learning, and deep learning in health care. She published two patents in the Patent Office Journal and one in Australian patent in the year 2018 and 2020, respectively. Currently, she is Principal Investigator of the project titled “Prognosis of Microaneurysm, and early diagnosis system for non-proliferative Diabetic Retinopathy using Deep Convolutional neural network” sponsored by SPARC-IITK, MHRD, Government of India, which is associated with University of California, Davis Campus, USA, and SRM IST, India, for 67 Lakhs in March 2019. She is author/co-author in 12 research articles in international journals and conferences,including SCI and Scopus indexed papers. She is Active Member of IEEE, ACM, and ISC.

 

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 InformaticsIEEE Transactions on Computational Social SystemsIEEE Internet of ThingsIEEE Intelligent SystemIEEE AccessACM 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

Publish with us