There has been rapid growth in biomedical engineering in recent decades, given advancements in medical imaging and physiological modelling and sensing systems, coupled with immense growth in computational and network technology, analytic approaches, visualization and virtual-reality, man-machine interaction and automation. Biomedical engineering involves applying engineering principles to the medical and biological sciences and it comprises several topics including biomedicine, medical imaging, physiological modelling and sensing, instrumentation, real-time systems, automation and control, signal processing, image reconstruction, processing and analysis, pattern recognition, and biomechanics. It holds great promise for the diagnosis and treatment of complex medical conditions, in particular, as we can now target direct clinical applications, research and development in biomedical engineering is helping us to develop innovative implants and prosthetics, create new medical imaging technologies and improve tools and techniques for the detection, prevention and treatment of diseases. The contributing authors in this edited book present representative surveys of advances in their respective fields, focusing in particular on techniques for the analysis of complex biomedical data. The book will be a useful reference for graduate students, researchers and industrial practitioners in computer science, biomedical engineering, and computational and molecular biology.

Handbook of Computational Intelligence in Biomedical Engineering and Healthcare helps readers analyze and conduct advanced research in specialty healthcare applications surrounding oncology, genomics and genetic data, ontologies construction, bio-memetic systems, biomedical electronics, protein structure prediction, and biomedical data analysis. The book provides the reader with a comprehensive guide to advanced computational intelligence, spanning deep learning, fuzzy logic, connectionist systems, evolutionary computation, cellular automata, self-organizing systems, soft computing, and hybrid intelligent systems in biomedical and healthcare applications. Sections focus on important biomedical engineering applications, including biosensors, enzyme immobilization techniques, immuno-assays, and nanomaterials for biosensors and other biomedical techniques. Other sections cover gene-based solutions and applications through computational intelligence techniques and the impact of nonlinear/unstructured data on experimental analysis. - Presents a comprehensive handbook that covers an Introduction to Computational Intelligence in Biomedical Engineering and Healthcare, Computational Intelligence Techniques, and Advanced and Emerging Techniques in Computational Intelligence - Helps readers analyze and do advanced research in specialty healthcare applications - Includes links to websites, videos, articles and other online content to expand and support primary learning objectives

Advances in Computational Techniques for Biomedical Image Analysis: Methods and Applications focuses on post-acquisition challenges such as image enhancement, detection of edges and objects, analysis of shape, quantification of texture and sharpness, and pattern analysis. It discusses the archiving and transfer of images, presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing. It examines various feature detection and segmentation techniques, together with methods for computing a registration or normalization transformation. Advances in Computational Techniques for Biomedical Image Analysis: Method and Applications is ideal for researchers and post graduate students developing systems and tools for health-care systems. - Covers various challenges and common research issues related to biomedical image analysis - Describes advanced computational approaches for biomedical image analysis - Shows how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. - Explores a range of computational algorithms and techniques, such as neural networks, fuzzy sets, and evolutionary optimization - Explores cloud based medical imaging together with medical imaging security and forensics

Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering progress and the ways they are aligning with the latest technologies in IoT and big data. In addition, the book includes various real-time/offline medical applications that directly or indirectly rely on medical and information technology. Case studies in the field of medical science, i.e., biomedical engineering, computer science, information security, and interdisciplinary tools, along with modern tools and the technologies used are also included to enhance understanding. Today, the role of Big Data and IoT proves that ninety percent of data currently available has been generated in the last couple of years, with rapid increases happening every day. The reason for this growth is increasing in communication through electronic devices, sensors, web logs, global positioning system (GPS) data, mobile data, IoT, etc. - Provides in-depth information about Biomedical Engineering with Big Data and Internet of Things - Includes technical approaches for solving real-time healthcare problems and practical solutions through case studies in Big Data and Internet of Things - Discusses big data applications for healthcare management, such as predictive analytics and forecasting, big data integration for medical data, algorithms and techniques to speed up the analysis of big medical data, and more

Arguably the first book of its kind, Computational Bioengineering explores the power of multidisciplinary computer modeling in bioengineering. Written by experts, the book examines the interplay of multiple governing principles underlying common biomedical devices and problems, bolstered by case studies. It shows you how to take advantage of the la

This book comprehensively and systematically treats modern understanding of the Nano-Bio-Technology and its therapeutic applications. The contents range from the nanomedicine, imaging, targeted therapeutic applications, experimental results along with modelling approaches. It will provide the readers with fundamentals on computational and modelling aspects of advanced nano-materials and nano-technology specifically in the field of biomedicine, and also provide the readers with inspirations for new development of diagnostic imaging and targeted therapeutic applications.

Computational Approaches in Bioengineering, Volume 2—Computational Approaches in Biomaterials and Biomedical Engineering Applications is a comprehensive and up-to-date resource that provides a broad overview of the use of computational methods in the fields of biomaterials and biomedical engineering. Written by a team of experts in the field of biomaterials and biomedical engineering, it provides a wealth of information on the use of computational methods in these fields. Furthermore, it explores emerging trends and discusses future directions and associated limitations in the field. Through thorough exploration and explanation, it showcases the latest research and advancements, offering valuable insights into how computational methods are utilized to design and optimize biomaterials, simulate biological processes, and develop innovative medical devices. FEATURES Provides practical guidance and real-world examples to help readers apply computational approaches effectively in their work Explores the diverse computational approaches employed in biomaterials and biomedical engineering applications, offering a comprehensive view of the field Introduces emerging topics and cutting-edge techniques, keeping wide range of readers at the forefront of advancements in computational bioengineering Discusses the integration of computational methods in biomaterials and biomedical engineering, fostering a deeper understanding of their synergistic potential Provides a valuable resource for researchers, practitioners, and students alike, serving as a comprehensive guide to computational approaches in biomaterials and biomedical engineering applications The book is well-organized and easy to read. The chapters are written in a clear and concise style, and they provide a comprehensive overview of the topics covered. The book is also well-illustrated with figures and tables that help to explain the concepts discussed in the text. With its comprehensive coverage, practical examples, and expert insights, this book serves as a valuable resource for researchers, students, and professionals in the fields of biomaterials and biomedical engineering.