Medical Imaging and Health Informatics (Next Generation Computing and Communication Engineering) - Hardcover

Hardcover

ISBN 10: 111981913X ISBN 13: 9781119819134

Publisher: Wiley-Scrivener, 2022

Synopsis

MEDICAL IMAGING AND HEALTH INFORMATICS

Provides a comprehensive review of artificial intelligence (AI) in medical imaging as well as practical recommendations for the usage of machine learning (ML) and deep learning (DL) techniques for clinical applications.

Medical imaging and health informatics is a subfield of science and engineering which applies informatics to medicine and includes the study of design, development, and application of computational innovations to improve healthcare. The health domain has a wide range of challenges that can be addressed using computational approaches; therefore, the use of AI and associated technologies is becoming more common in society and healthcare. Currently, deep learning algorithms are a promising option for automated disease detection with high accuracy. Clinical data analysis employing these deep learning algorithms allows physicians to detect diseases earlier and treat patients more efficiently. Since these technologies have the potential to transform many aspects of patient care, disease detection, disease progression and pharmaceutical organization, approaches such as deep learning algorithms, convolutional neural networks, and image processing techniques are explored in this book.

This book also delves into a wide range of image segmentation, classification, registration, computer-aided analysis applications, methodologies, algorithms, platforms, and tools; and gives a holistic approach to the application of AI in healthcare through case studies and innovative applications. It also shows how image processing, machine learning and deep learning techniques can be applied for medical diagnostics in several specific health scenarios such as COVID-19, lung cancer, cardiovascular diseases, breast cancer, liver tumor, bone fractures, etc. Also highlighted are the significant issues and concerns regarding the use of AI in healthcare together with other allied areas, such as the Internet of Things (IoT) and medical informatics, to construct a global multidisciplinary forum.

Audience
The core audience comprises researchers and industry engineers, scientists, radiologists, healthcare professionals, data scientists who work in health informatics, computer vision and medical image analysis.

About this title

About the Author

Tushar H. Jaware, PhD, received his degree in Medical Image Processing and is now an assistant professor in the Department of Electronics and Telecommunication Engineering, R C Patel Institute of Technology, Shirpur, India. He has published more than 50 research articles in refereed journals and IEEE conferences, and has three international patents granted and two Indian patents published.

K. Sarat Kumar, PhD, received his degree in Electronics Engineering and is now a professor in the Department of Electronics & Communication Engineering, K L University, Andhra Pradesh, India.

Ravindra D. Badgujar, PhD, received his degree in Electronics Engineering and is now an assistant professor in the Department of Electronics and Telecommunication Engineering, R C Patel Institute of Technology, Shirpur, India. He has published many research articles in refereed journals and IEEE conferences as well as one international patent granted and two Indian patents published.

Svetlin Antonov, PhD, received his degree in Telecommunications and is now a lecturer in the Faculty of Telecommunications, TU-Sofia, Bulgaria. He is the author of several books and more than 60 peer-reviewed articles.

From the Back Cover

Provides a comprehensive review of artificial intelligence (AI) in medical imaging as well as practical recommendations for the usage of machine learning (ML) and deep learning (DL) techniques for clinical applications.

Medical imaging and health informatics is a subfield of science and engineering which applies informatics to medicine and includes the study of design, development, and application of computational innovations to improve healthcare. The health domain has a wide range of challenges that can be addressed using computational approaches; therefore, the use of AI and associated technologies is becoming more common in society and healthcare. Currently, deep learning algorithms are a promising option for automated disease detection with high accuracy. Clinical data analysis employing these deep learning algorithms allows physicians to detect diseases earlier and treat patients more efficiently. Since these technologies have the potential to transform many aspects of patient care, disease detection, disease progression and pharmaceutical organization, approaches such as deep learning algorithms, convolutional neural networks, and image processing techniques are explored in this book.

This book also delves into a wide range of image segmentation, classification, registration, computer-aided analysis applications, methodologies, algorithms, platforms, and tools; and gives a holistic approach to the application of AI in healthcare through case studies and innovative applications. It also shows how image processing, machine learning and deep learning techniques can be applied for medical diagnostics in several specific health scenarios such as COVID-19, lung cancer, cardiovascular diseases, breast cancer, liver tumor, bone fractures, etc. Also highlighted are the significant issues and concerns regarding the use of AI in healthcare together with other allied areas, such as the Internet of Things (IoT) and medical informatics, to construct a global multidisciplinary forum.

Audience
The core audience comprises researchers and industry engineers, scientists, radiologists, healthcare professionals, data scientists who work in health informatics, computer vision and medical image analysis.

Edition details

• Publisher: Wiley-Scrivener
• Publication date: 2022
• Language: English
• ISBN 10: 111981913X
• ISBN 13: 9781119819134
• Binding: Hardcover
• Edition number: 1
• Number of pages: 384
• Editor: Jaware Tushar H., Kumar K. Sarat, Badgujar Ravindra D., Antonov Svetlin