Handbook of Deep Learning in Biomedical Engineering and Health Informatics

This new volume discusses state-of-the-art deep learning techniques and approaches that can be applied in biomedical systems and health informatics. Deep learning in the biomedical field is an effective method of collecting and analyzing data that can be used for the accurate diagnosis of disease.

This volume delves into a variety of applications, techniques, algorithms, platforms, and tools used in this area, such as image segmentation, classification, registration, and computer-aided analysis. The editors proceed on the principle that accurate diagnosis of disease depends on image acquisition and interpretation. There are many methods to get high resolution radiological images, but we are still lacking in automated image interpretation. Currently deep learning techniques are providing a feasible solution for automatic diagnosis of disease with good accuracy. Analyzing clinical data using deep learning techniques enables clinicians to diagnose diseases at an early stage and treat the patients more effectively.

Chapters explore such approaches as deep learning algorithms, convolutional neural networks and recurrent neural network architecture, image stitching techniques, deep RNN architectures, and more. The volume also depicts how deep learning techniques can be applied for medical diagnostics of several specific health scenarios, such as cancer, COVID-19, acute neurocutaneous syndrome, cardiovascular and neuro diseases, skin lesions and skin cancer, etc.

Key features:

• Introduces important recent technological advancements in the field
• Describes the various techniques, platforms, and tools used in biomedical deep learning systems
• Includes informative case studies that help to explain the new technologies

Handbook of Deep Learning in Biomedical Engineering and Health Informatics

provides a thorough exploration of biomedical systems applied with deep learning techniques and will provide valuable information for researchers, medical and industry practitioners, academicians, and students.

E. Golden Julie, PhD, is a Senior Assistant Professor in the Department of Computer Science and Engineering at Anna University, Regional Campus, in Tirunelveli, India. She ?has? more than? 12 ?years? of? experience ?in ?teaching and? has? published? more ?than? 34 ?papers ?in? various? international? journals. Dr. Julie has also presented ?more? than? 20 ?papers ?at? ?national ?and ?international? conferences.? She ?has? written? ten book chapters and is acting as an editor for the book Successful Implementation and Deployment of IoT Projects in Smart Cities, to be published by IGI Global in the Advances in Environmental Engineering and Green Technologies book series. She is one of the editors for the book Handbook of Research on Blockchain Technology: Trend and Technologies, published by Elsevier. She ?also acts as? a? reviewer? for? many journals on computers and electrical engineering. Dr. Julie has? given? many guest? lectures ?in ?various ?subjects?, such? as? multicore ?architecture,? operating systems, compiler design, etc. She is a recognized reviewer and translator for the NPTEL Online (MOOC) courses certificate from the National Programme on Technology Enhanced Learning. She? has ?acted ?as ?a? jury? member at the national? and international levels at IEEE conferences, ?project ?fairs, and symposia?.

Y. Harold Robinson, PhD, is currently working at the School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India. He? has? more? than ?15 ?years? of? experience ?in ?teaching and has published? more ?than? 50 ?papers ?in? various? international? journals. He has presented ?more? than? 45 ?papers ?in? both ?national ?and ?international? conferences.? He? has? written? four book chapters published in books by Springer? and IGI.? Dr. Robinson is acting as an editor for a book Successful Implementation and Deployment of IoT Projects in Smart Cities, published by IGI Global in the Advances in Environmental Engineering and Green Technologies book series. He is one of the editors for the book Handbook of Research on Blockchain Technology: Trend and Technologies, published by Elsevier. He? has? given? many guest? lectures ?in ?various ?subjects,? such? as pointer,? operating system, compiler design, etc.? and has? also? given ?an? invited ?talk? at a ?technical symposium. He? has ?acted ?as ?a? convenor, coordinator,? and jury member for IEEE conferences, ?project? fairs, and symposia. His? research ?areas ?includes ?wireless? sensor? networks, ad-hoc? networks, soft computing, blockchain, IoT, ?and ?image? processing. He ?is ?a reviewer? of? many journals, including Multimedia Tools and Applications, and has also published research papers in various SCIE journals.

S. M. Jaisakthi, PhD, is an Associate Professor at the School of Computer Science and Engineering at the Vellore Institute of Technology, India. Dr. Jaisakthi has extensive research experience in machine learning in the area of image processing and medical image analysis. She also has significant experience in building deep learning models, including convolutional (CNN) and recurrent neural networks (RNN). She has published many research publications in refereed international journals and in proceedings of international conferences. Currently she is investigating a project funded by the Science and Engineering Research Board (SERB).