The text presents a compilation of research and methodologies at the intersection of thermal imaging, medical diagnostics, and artificial intelligence for non-invasive early disease detection, diagnosis, and monitoring across a spectrum of medical conditions. It highlights the importance of using the latest technologies to improve performance, productivity, efficiency, and security in healthcare without sacrificing reliability or accessibility. The structured chapters provide both foundational and advanced insights into the use of infrared thermography in breast thermogram analysis, osteoporosis detection, cancer research, diabetic neuropathy, oral cancer, and skin lesions, emphasizing how computational intelligence augments diagnostic precision.
This book:
- Covers the application of thermograms in the early detection of various diseases using faster and more efficient image processing, and intelligent classification algorithms.
- Discusses the use of different image processing methods in thermal imaging applications to diagnose various medical issues.
- Focuses on implementing the latest artificial intelligence techniques including machine learning to automate the decisions based on thermograms to aid medical experts in quick and effective diagnosis with early detection of diseases.
- Presents an in-depth analysis of the application of infrared thermal imaging in the diagnosis of specific diseases like cancer, Osteoporosis, skin lesions, and diabetic neuropathy focusing on the computational techniques.
It is primarily written for senior undergraduates, graduate students, and academic researchers in medicine, bioengineering, electrical engineering, electronics and communications engineering, computer science engineering, and biomedical engineering.
Table of Contents:
1. Harnessing Machine Learning for Breast Thermogram Analysis: Advancements in Early Detection and Diagnosis. 2. Automatic Detection of Osteoporosis using Explainable AI Techniques. 3. Ensemble Machine Learning classification for breast thermograms. 4. Transforming Cancer Research: Early Detection Using Thermal Imaging and Machine Learning. 5. Infrared Thermal Imaging In Diabetic Neuropathy. 6. Integration of Computational intelligence and Thermal Imaging for Enhanced Skin Lesion Diagnosis. 7. A comprehensive overview of advancing Oral Cancer Detection: The Role of Thermal Imaging and Artificial Intelligence. 8. Ocular Surface Temperature Measurements in Diabetic Retinopathy Affected Patients using Infrared Thermal Imaging. 9. From History to Modernity: Agnikarma Procedure and its Evaluation with Technical Methodologies. 10. A Comprehensive Framework for the Detection and Management of Diabetic Foot Ulcers Using Diverse Imaging Techniques. 11. Identification of Jaundice-affected and normal infants in NICUs from the clinical image dataset using deep learning models. 12. Thermogram Analysis from an Image Processing Perspective. 13. Convolutional Neural Networks for Early Disease Detection in AI-Powered Thermographic Imaging. 14. A Comprehensive Review of Machine Learning and Deep Learning Techniques for Early Detection of Alzheimer’s and Dementia
About the Author :
Neha Singh is currently working as Assistant Professor, in the Department of Electronics & Communication Engineering at Manipal University Jaipur, Rajasthan, India. She completed her PhD in image processing in 2020 and has more than 20 years of experience in academics. Her areas of research interest include Image processing, Machine learning, VLSI design and nanodevices. She has several papers and book chapters published in Journals and conferences of repute. She has 1 patent and has served as reviewer in various International and peer reviewed Journals and conferences of repute. She has also worked as Convener, Session Chair and organizer of various international conferences, summer internships in Diode Fabrication and Faculty Development Programs. She has guided several M Tech Dissertations and B Tech projects and presently guiding UG and doctoral students. She is presently a Senior Member of IEEE. She has authored engineering textbooks as well as served as editors for three edited books on Nanotechnology, Low power circuits and devices intelligent techniques for predictive data analytics. Some other edited books are in progress in the area of AI and VLSI.
Shashi Kant Dargar is currently working as an Associate Professor in the Electronics & Communication Engineering Department at Kalasalingam Academy of Research and Education, Tamilnadu, India. He received his Ph.D. degree (2017) in microelectronics, Master's (2013) in digital communication, and Bachelor's (2005) in electronics and communication engineering. He completed his three-year post-doctoral research in electronic engineering at the University of KwaZulu-Natal, Durban, South Africa. He has contributed to research and academics for 16 years, including microelectronics, thin-film device design, VLSI, wireless communication, and microwave & communication engineering. He taught Analog Integrated circuits, VLSI signal processing, VLSI Technology, Analog Devices, Circuits, Signals and Systems, Digital Signal Processing, Communications and Low Power VLSI design. At the postgraduate level, Thin Film Electronics, Flexible Electronics, Sensor devices, Microwave and Communication, Semiconductor Device Modelling and Quantum electronics. He has authored 41 scientific research articles in reputed journals and conferences. He is a Senior Member of IEEE and Life Member of IEEE HKN- Mu Eta Chapter.
Shilpi Birla is working as an Associate Professor in Electronics & Communication Department at Manipal University Jaipur. She has a teaching and industrial experience of more than 16 years. She did her Ph D in Low Power VLSI Design. Her research interests are Low Power VLSI Design, Memory Circuits, Digital VLSI Circuits, Nanodevices and Image Processing. She has authored more than 60 research papers in journals of repute and International conferences. She has organized several workshops in HSPICE, TCAD and XILINX, Summer internships in Diode Fabrication and Faculty Development Programs. She has worked as a session chair, conference steering committee member, editorial board member, and reviewer in international/national IEEE Journal and conferences. She has guided many M. Tech Students and guiding Ph.D. students. She is a senior member of IEEE.
Josephine Selle Jeyanathan is working as an Associate Professor in the Department of Electronics and Communication Engineering at Kalasalingam Academy of Research and Education (Kalasalingam University), Krishnankoil, India since 2016. She graduated in Electronics and Communication Engineering from Karunya University and post-graduated in Communication Systems in 2011 from Anna University, Chennai, India. She received her Ph.D under the faculty of Information and Communication Engineering at Anna University, Chennai. Her thesis title is “Some Studies on Analysis of Breast Thermograms Using Pattern Classification”. She has published two book chapters and several technical research papers in reputed International Journals and IEEE Conferences. Her areas of interest are Medical Image Processing, Soft computing techniques, and Pattern Classification for breast thermograms. She has worked in a sponsored project by Indira Gandhi Centre for Atomic Research (IGCAR), Kalpakkam from 2012-to 2015. Also, she is a professional member of IEEE and a life member of the Biomedical Engineering Society for India.
