Machine Learning and Deep Learning Techniques for Medical Science

413 Pages·2022·40.71 MB·English

by  K. Gayathri Devi, Kishore Balasubramanian, Le Anh Ngoc

MACHINE LEARNING
AND DEEP LEARNING
TECHNIQUES FOR
MEDICAL SCIENCE
Artificial Intelligence (AI): Elementary to Advanced
Practices
Series Editors: Vijender Kumar Solanki, Zhongyu (Joan) Lu, and
Valentina E Balas
In the emerging smart city technology and industries, the role of artificial intelligence is
getting more prominent. This AI book series will aim to cover the latest AI work, which
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AI practitioners it will assist in shedding light on new avenues in the AI domains. The
series will cover the recent work carried out in AI and its associated domains; it will cover
Logics, Pattern Recognition, NLP, Expert Systems, Machine Learning, Block-Chain, and
Big Data. The work domain of AI is quite deep, so it will be covering the latest trends that
are evolving with the concepts of AI and it will be helping those new to the field, prac-
titioners, students, as well as researchers, to gain some new insights.
Enabling Technologies for Next Generation Wireless Communications
Edited by Mohammed Usman, Mohd Wajid, and Mohd Dilshad Ansari
Artificial Intelligence (AI)
Recent Trends and Applications
Edited by S. Kanimozhi Suguna, M. Dhivya, and Sara Paiva
Deep Learning for Biomedical Applications
Edited by Utku Kose, Omer Deperlioglu, and D. Jude Hemanth
Cybersecurity
Ambient Technologies, IoT, and Industry 4.0 Implications
Gautam Kumar, Om Prakash Singh, and Hemraj Saini
Industrial Internet of Things
Technologies, Design, and Applications
Edited by Sudan Jha, Usman Tariq, Gyanendra Prasad Joshi, and
Vijender Kumar Solanki
Machine Learning And Deep Learning Techniques For Medical Science
Edited by K. Gayathri Devi, Kishore Balasubramanian and Le Anh Ngoc
For more information on this series, please visit: https://www.routledge.com/Artificial-
Intelligence-AI-Elementary-to-Advanced-Practices/book-series/CRCAIEAP
MACHINE LEARNING
AND DEEP LEARNING
TECHNIQUES FOR
MEDICAL SCIENCE
Edited by
K. Gayathri Devi, Kishore Balasubramanian,
and Le Anh Ngoc
MATLAB® is a trademark of The MathWorks, Inc. and is used with permission. The MathWorks does not
warrant the accuracy of the text or exercises in this book. This book’s use or discussion of MATLAB®
software or related products does not constitute endorsement or sponsorship by The MathWorks of a
particular pedagogical approach or particular use of the MATLAB® software.
First edition published 2022
by CRC Press
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and by CRC Press
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CRC Press is an imprint of Taylor & Francis Group, LLC
© 2022 selection and editorial matter, K. Gayathri Devi, Kishore Balasubramanian, and Le Anh
Ngoc; individual chapters, the contributors
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Library of Congress Cataloging‑in‑Publication Data
Names: Gayathri Devi, K. G., editor.
Title: Machine learning and deep learning techniques for medical science / edited by K. Gayathri Devi,
Kishore Balasubramanian, Le Anh Ngoc.
Description: First edition. | Boca Raton : CRC Press, 2022. |
Series: Artificial intelligence (AI): elementary to advanced practices | Includes bibliographical
references and index. |
Summary: “This book presents the integration of machine learning and deep learning algorithms that
can be applied in the healthcare sector to reduce the time needed by doctors, radiologists, and other
medical professionals to analyze, predict, and diagnose conditions with accurate results”‐‐ Provided
by publisher.
Identifiers: LCCN 2021059672 (print) | LCCN 2021059673 (ebook) | ISBN 9781032104201
(hardback) | ISBN 9781032108827 (paperback) | ISBN 9781003217497 (ebook)
Subjects: LCSH: Medical informatics. | Machine learning. | Deep learning (Machine learning) |
Artificial intelligence‐‐Medical applications. | Medical technology.
Classification: LCC R858 .M316 2022 (print) | LCC R858 (ebook) | DDC 610.285‐‐dc23/eng/20220120
LC record available at https://lccn.loc.gov/2021059672
LC ebook record available at https://lccn.loc.gov/2021059673
ISBN: 978-1-032-10420-1 (hbk)
ISBN: 978-1-032-10882-7 (pbk)
ISBN: 978-1-003-21749-7 (ebk)
DOI: 10.1201/9781003217497
Typeset in Times
by MPS Limited, Dehradun
Contents
Editor Biographies..................................................................................................ix
List of Contributors...............................................................................................xi
Chapter 1 A Comprehensive Study on MLP and CNN, and the
Implementation of Multi-Class Image Classification using
Deep CNN...........................................................................................1
S. P. Balamurugan
Chapter 2 An Efficient Technique for Image Compression and
Quality Retrieval in Diagnosis of Brain Tumour Hyper
Spectral Image.................................................................................27
V. V. Teresa, J. Dhanasekar, V. Gurunathan, and
T. Sathiyapriya
Chapter 3 Classification of Breast Thermograms using a Multi-layer
Perceptron with Back Propagation Learning..............................45
Aayesha Hakim and R. N. Awale
Chapter 4 Neural Networks for Medical Image Computing........................75
V. A. Pravina, P. K. Poonguzhali, and A. Kishore Kumar
Chapter 5 Recent Trends in Bio-Medical Waste, Challenges and
Opportunities...................................................................................97
S. Kannadhasan and R. Nagarajan
Chapter 6 Teager-Kaiser Boost Clustered Segmentation of Retinal
Fundus Images for Glaucoma Detection....................................109
P M Siva Raja, R P Sumithra, and K Ramanan
Chapter 7 IoT-Based Deep Neural Network Approach for Heart
Rate and SpO Prediction............................................................121
2
Madhusudan G. Lanjewar, Rajesh K. Parate,
Rupesh D. Wakodikar, and Anil J. Thusoo
v
vi Contents
Chapter 8 An Intelligent System for Diagnosis and Prediction of Breast
Cancer Malignant Features using Machine Learning
Algorithms......................................................................................143
Ritu Aggarwal
Chapter 9 Medical Image Classification with Artificial and Deep
Convolutional Neural Networks: A Comparative Study..........153
Amen Bidani, Mohamed Salah Gouider, and
Carlos M Travieso-Gonzalez
Chapter 10 Convolutional Neural Network for Classification of Skin
Cancer Images...............................................................................175
Giang Son Tran, Quoc Viet Kieu, and Thi Phuong Nghiem
Chapter 11 Application of Artificial Intelligence in Medical Imaging........195
Sampurna Panda and Rakesh Kumar Dhaka
Chapter 12 Machine Learning Algorithms Used in Medical Field
with a Case Study..........................................................................203
M. Jayasanthi and R. Kalaivani
Chapter 13 Dual Customized U-Net-based Based Automated Diagnosis
of Glaucoma...................................................................................221
C. Thirumarai Selvi, J. Amudha, and R. Sudhakar
Chapter 14 MuSCF-Net: Multi-scale, Multi-Channel Feature Network
using Resnet-Based Attention Mechanism for Breast
Histopathological Image Classification.......................................243
Meenakshi M. Pawer, Suvarna D. Pujari, Swati P. Pawar, and
Sanjay N. Talbar
Chapter 15 Artificial Intelligence is Revolutionizing Cancer Research......263
B. Sudha, K. Suganya, K. Swathi, and S. Sumathi
Chapter 16 Deep Learning to Diagnose Diseases and Security in 5G
Healthcare Informatics.................................................................279
Partha Ghosh
Contents vii
Chapter 17 New Approaches in Machine-based Image Analysis for
Medical Oncology..........................................................................333
E. Francy Irudaya Rani, T. LurthuPushparaj,
E. Fantin Irudaya Raj, and M. Appadurai
Chapter 18 Performance Analysis of Deep Convolutional Neural Networks
for Diagnosing COVID-19: Data to Deployment......................361
K. Deepti
Chapter 19 Stacked Auto Encoder Deep Neural Network with Principal
Components Analysis for Identification of Chronic Kidney
Disease.............................................................................................385
Sanat Kumar Sahu and Pratibha Verma
Index......................................................................................................................397

Editor Biographies
Dr. K. Gayathri Devi has 21 years of experience working as a Professor in the
Department of Electronics and Communication Engineering, Dr. N.G.P Institute of
Technology, Tamil Nadu, India. She received her B.E. degree in ECE from Coimbatore
Institute of Technology (1998), and M.E degree from Dr Mahalingam College of
Engineering and Technology, (2005) and Ph.D. from Medical Image Processing (2016)
under the affiliation of Anna University, Chennai. She has published 3 patents, 26 papers,
3 book chapters, and 24 conference publications. She is an editor of the book “Artificial
Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning
Approaches” published by CRC Press, Taylor & Francis Group. She is also a reviewer of
several SCI and Scopus indexed journals. She has completed 21 online certification
courses from NPTEL, Coursera, Mathworks and Great Learning and Topper in the
NPTEL courses “Digital Image Processing of Remote Sensing Images” and “Outcome
based pedagogic principles for effective teaching”. Received Grant from Anna University
Chennai and ICMR to conduct programmes. She is a life member in ISTE, IETE and
IAENG.
Dr. Kishore Balasubramanian has more than 17 years of academic experience in
imparting Engineering Education. He received his Bachelor’s Degree in Electronics and
Instrumentation from Bharathiar University, India, Master’s Degree in Applied
Electronics from Anna University, India and Ph.D. (Information and Communication
Engineering) from Anna University, India. His research interests include Medical Image
Processing and Computer Vision. He is an active reviewer in many SCI and Scopus
indexed journals, conferences and editor in several scientific international journals. He
has authored three books in the field of Analog Electronics and has published papers in
international and national journals. He has received grants from CSIR, DRDO
(Government Funding agencies) for conducting Faculty Development Programmes,
Workshops and Conferences. He is a member of ISTE, IRED and IAENG. Presently he
is working as an Assistant Professor (Senior Scale) in the Department of EEE and holds
the additional portfolio as Training Officer (Career Planning and Guidance Cell) at Dr.
Mahalingam College of Engineering & Technology, India.
Dr. Le Anh Ngoc is a Director of Swinburne Innovation Space, Swinburne University of
Technology (Vietnam). He received his B.S in Mathematics and Informatics from Vinh
University and VNU University of Science, Master’s degree in Information Technology
from Hanoi University of Technology, Vietnam, and Ph.D. degree in Communication
and Information Engineering from the School of Electrical Engineering and Computer
Science, Kyungpook National University, South Korea, in 2009. His general research
interests are Embedded and Intelligent Systems, Communication Networks, the Internet
of Things, Image/Video Processing, AI & Big Data Analysis. On these topics, he
published more than 60 papers in International journals and Conference proceedings. He
served as a Keynote Speaker, TPC member, Session chair, Book Editor, and Reviewer of
The international conferences and journals (Email: [email protected]).
ix