Information Physics: Physics-Information and Quantum Analogies for Complex Modeling presents a new theory of complex systems that uses analogy across various aspects of physics, including electronics, magnetic circuits and quantum mechanics. The book explains the quantum approach to system theory that can be understood as an extension of classical system models. The main idea is that in many complex systems there are incomplete pieces of overlapping information that must be strung together to find the most consistent model. This incomplete information can be understood as a set of non-exclusive observer results. Because they are non-exclusive, each observer registers different pictures of reality.

This book comprises a collection of papers presented at the International Workshop on New Approaches for Multidimensional Signal Processing (NAMSP 2021), held at Technical University of Sofia, Sofia, Bulgaria, during 08-10 July 2021. The book covers research papers in the field of N-dimensional multicomponent image processing, multidimensional image representation and super-resolution, 3D image processing and reconstruction, MD computer vision systems, multidimensional multimedia systems, neural networks for MD image processing, data-based MD image retrieval and knowledge data mining, watermarking, hiding and encryption of MD images, MD image processing in robot systems, tensor-based data processing, 3D and multi-view visualization, forensic analysis systems for MD images and many more.

This book introduces modeling and simulation of linear time invariant systems and demonstrates how these translate to systems engineering, mechatronics engineering, and biomedical engineering. It is organized into nine chapters that follow the lectures used for a one-semester course on this topic, making it appropriate for students as well as researchers. The author discusses state space modeling derived from two modeling techniques and the analysis of the system and usage of modeling in control systems design. It also contains a unique chapter on multidisciplinary energy systems with a special focus on bioengineering systems and expands upon how the bond graph augments research in biomedical and bio-mechatronics systems.

This book provides a comprehensive overview of the design, generation and characterization of minimal cell systems. Written by leading experts, it presents an in-depth analysis of the current issues and challenges in the field, including recent advances in the generation and characterization of reduced-genome strains generated from model organisms with relevance in biotechnology, and basic research such as Escherichia coli, Corynebacterium glutamicum and yeast. It also discusses methodologies, such as bottom-up and top-down genome minimization strategies, as well as novel analytical and experimental approaches to characterize and generate minimal cells. Lastly, it presents the latest research related to minimal cells of serveral microorganisms, e.g. Bacillus subtilis. The design of biological systems for biotechnological purposes employs strategies aimed at optimizing specific tasks. This approach is based on enhancing certain biological functions while reducing other capacities that are not required or that could be detrimental to the desired objective. A highly optimized cell factory would be expected to have only the capacity for reproduction and for performing the expected task. Such a hypothetical organism would be considered a minimal cell. At present, numerous research groups in academia and industry are exploring the theoretical and practical implications of constructing and using minimal cells and are providing valuable fundamental insights into the characteristics of minimal genomes, leading to an understanding of the essential gene set. In addition, research in this field is providing valuable information on the physiology of minimal cells and their utilization as a biological chassis to which useful biotechnological functions can be added.

This book presents novel and advanced topics in Medical Image Processing and Computational Vision in order to solidify knowledge in the related fields and define their key stakeholders. It contains extended versions of selected papers presented in VipIMAGE 2013 - IV International ECCOMAS Thematic Conference on Computational Vision and Medical Image, which took place in Funchal, Madeira, Portugal, 14-16 October 2013. The twenty-two chapters were written by invited experts of international recognition and address important issues in medical image processing and computational vision, including: 3D vision, 3D visualization, colour quantisation, continuum mechanics, data fusion, data mining, face recognition, GPU parallelisation, image acquisition and reconstruction, image and video analysis, image clustering, image registration, image restoring, image segmentation, machine learning, modelling and simulation, object detection, object recognition, object tracking, optical flow, pattern recognition, pose estimation, and texture analysis. Different applications are addressed and described throughout the book, comprising: biomechanical studies, bio-structure modelling and simulation, bone characterization, cell tracking, computer-aided diagnosis, dental imaging, face recognition, hand gestures detection and recognition, human motion analysis, human-computer interaction, image and video understanding, image processing, image segmentation, object and scene reconstruction, object recognition and tracking, remote robot control, and surgery planning. This volume is of use to researchers, students, practitioners and manufacturers from several multidisciplinary fields, such as artificial intelligence, bioengineering, biology, biomechanics, computational mechanics, computational vision, computer graphics, computer science, computer vision, human motion, imagiology, machine learning, machine vision, mathematics, medical image, medicine, pattern recognition, and physics.

This book introduces a variety of well-proven and newly developed nature-inspired optimization algorithms solving a wide range of real-life biomedical and healthcare problems. Few solo and hybrid approaches are demonstrated in a lucid manner for the effective integration and finding solution for a large-scale complex healthcare problem. In the present bigdata-based computing scenario, nature-inspired optimization techniques present adaptive mechanisms that permit the understanding of complex data and altering environments. This book is a voluminous collection for the confront faced by the healthcare institutions and hospitals for practical analysis, storage, and data analysis. It explores the distinct nature-inspired optimization-based approaches that are able to handle more accurate outcomes for the current biomedical and healthcare problems. In addition to providing a state-of-the-art and advanced intelligent methods, it also enlightens an insight for solving diversified healthcare problems such as cancer and diabetes.

Data Science for COVID-19 presents leading-edge research on data science techniques for the detection, mitigation, treatment and elimination of COVID-19. Sections provide an introduction to data science for COVID-19 research, considering past and future pandemics, as well as related Coronavirus variations. Other chapters cover a wide range of Data Science applications concerning COVID-19 research, including Image Analysis and Data Processing, Geoprocessing and tracking, Predictive Systems, Design Cognition, mobile technology, and telemedicine solutions. The book then covers Artificial Intelligence-based solutions, innovative treatment methods, and public safety. Finally, readers will learn about applications of Big Data and new data models for mitigation.

Thermal Ablation Therapy: Theory and Simulation includes detailed theoretical and technical concepts of thermal ablation therapy in different body organs. Concepts of ablation technology based on different thermal ablation methods are introduced, along with changes in the tissues' mechanical properties due to thermal denaturation. The book emphasizes the mathematical and engineering concepts of RF and MW energy propagation through tissues and where high heating rates produced by MW systems can overcome the heat-sink effects from nearby vessels. The design and tuning of the MW antennas to deliver energy efficiently to specific organ systems such as the liver or lung is also covered. Other sections cover the computational modeling of radiofrequency ablation and microwave ablation procedures for developing and implementing new efficient ablation in clinical systems, numerical simulations for different scenarios of different organs with different size using RF and MW ablation systems with different antennas'/probes design and configurations, and numerical techniques for temperature profile in tissues.

Autonomous Robot-Aided Optical Manipulation for Biological Cells gives a systematically and almost self-contained description of the many facets of modeling, sensing, and control techniques or experimentally exploring emerging trends in optical manipulation of biological cell in micro/nanorobotics systems. To achieve biomedical applications, reliability design, modeling, and precision control are vitally important for the development of engineering systems. With the advances in modeling, sensing, and control techniques, it is opportunistic to exploit them for the benefit of reliability design, actuation, and precision control of micro/nanomanipulation systems to expanding the applications of robot at the micro and nano scales, especially in biomedical engineering. This book presents new techniques in reliability modeling and advanced control of robot-aided optical manipulation of biological cells systems. The book will be beneficial to the researchers within robotics, mechatronics, biomedical engineering, and automatic control society, including both academic and industrial parts.

This book examines the role of nanobiosensors in point-of-care applications for personalized healthcare and management. It begins by discussing various biomaterials that are used for the development of biosensors in medical diagnostics, and reviews advances in their fabrication and the miniaturization of biosensor devices for lab-on-chip analysis. In turn, it explores the rapidly evolving applications of nanomaterials in the context of biomaterial diagnostics. The book also explores the immense potential of biosensors in medical diagnostics, where they are increasingly being used to detect a wide range of biomolecules and biomarkers. In closing, it discusses the current challenges and outlines the future role of nanobiosensors in the development of next-generation point-of-care applications.

This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.

The goal of this volume is to summarize the state-of-the-art in the utilization of computer vision techniques in the diagnosis of skin cancer. Malignant melanoma is one of the most rapidly increasing cancers in the world. Early diagnosis is particularly important since melanoma can be cured with a simple excision if detected early. In recent years, dermoscopy has proved valuable in visualizing the morphological structures in pigmented lesions. However, it has also been shown that dermoscopy is difficult to learn and subjective. Newer technologies such as infrared imaging, multispectral imaging, and confocal microscopy, have recently come to the forefront in providing greater diagnostic accuracy. These imaging technologies presented in this book can serve as an adjunct to physicians and provide automated skin cancer screening. Although computerized techniques cannot as yet provide a definitive diagnosis, they can be used to improve biopsy decision-making as well as early melanoma detection, especially for patients with multiple atypical nevi.

Features: • Provides an accessible introduction to the subject. • Up to date with the latest advances in emerging technologies and procedures. • Provides a historical overview of CT technology.

This book reports on the latest advances in the study of biomedical signal processing, and discusses in detail a number of open problems concerning clinical, biomedical and neural signals. It methodically collects and presents in a unified form the research findings previously scattered throughout various scientific journals and conference proceedings. In addition, the chapters are self-contained and can be read independently. Accordingly, the book will be of interest to university researchers, R&D engineers and graduate students who wish to learn the core principles of biomedical signal analysis, algorithms, and applications, while also offering a valuable reference work for biomedical engineers and clinicians who wish to learn more about the theory and recent applications of neural engineering and biomedical signal processing.

Although many radiation protection scientists and engineers use dose coefficients, few know the origin of those dose coefficients. This is the first book in over 40 years to address the topic of radiation protection dosimetry in intimate detail. Advanced Radiation Protection Dosimetry covers all methods used in radiation protection dosimetry, including advanced external and internal radiation dosimetry concepts and regulatory applications. This book is an ideal reference for both scientists and practitioners in radiation protection and students in graduate health physics and medical physics courses. Features: A much-needed book filling a gap in the market in a rapidly expanding area Contains the history, evolution, and the most up-to-date computational dosimetry models Authored and edited by internationally recognized authorities and subject area specialists Interrogates both the origins and methodologies of dose coefficient calculation Incorporates the latest international guidance for radiation dosimetry and protection

Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks.

Nanotechnology is expected to bring revolutionary changes in a variety of fields. This volume describes nanoparticles and their biomedical applications, and covers metal nanoparticles, metal oxide nanoparticles, rare earth based nanoparticles and graphene oxide nanoparticles. It elaborates on a number of biomedical applications, including therapeutic applications. It addresses the topic of green synthesis, in view of increasing health and environmental concerns.

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.

Highlights the utilization of nanofillers. Investigates the moisture absorption and ageing on the physio-chemical, mechanical, thermal properties of the vinyl ester-based composites. Considers the influence of hybridization, fibre architecture, and fibre-ply orientation on the mechanical and thermal properties of vinyl ester-based biocomposites. Discusses the effects of the alkali treatment. Chapters are written by global experts to cover a diverse scope of industry applications for fibre-reinforced polymer composites.

Structural Biomaterials: Properties, Characteristics, and Selection serves as a single point of reference to digest current research and develop a deeper understanding in the field of biomaterials engineering. This book uses a materials-focused approach, allowing the reader to quickly access specific, detailed information on biomaterials characterization and selection. Relevant to a range of readers, this book provides holistic coverage of the broad categories of structural biomaterials currently available and used in medical applications, highlighting the property requirements for structural biomaterials, their biocompatibility performance and their safety regulation in key categories such as metals, ceramics and polymers. The materials science perspective of this text ensures the content is accessible even to those without an extensive background in applied medicine, positioning this text not just for students, but as an overview and reference for researchers, scientists and engineers entering the field from related materials science disciplines.

Handbook of Decision Support Systems for Neurological Disorders provides readers with complete coverage of advanced computer-aided diagnosis systems for neurological disorders. While computer-aided decision support systems for different medical imaging modalities are available, this is the first book to solely concentrate on decision support systems for neurological disorders. Due to the increase in the prevalence of diseases such as Alzheimer, Parkinson's and Dementia, this book will have significant importance in the medical field. Topics discussed include recent computational approaches, different types of neurological disorders, deep convolution neural networks, generative adversarial networks, auto encoders, recurrent neural networks, and modified/hybrid artificial neural networks.

Web Semantics strengthen the description of web resources to exploit them better and make them more meaningful for both humans and machines, thereby contributing to the development of a knowledgeintensive data web. The world is experiencing the movement of concept from data to knowledge and the movement of web from document model to data model. The underlying idea is making the data machine understandable and processable. In the light of these trends, conciliation of Semantic and the Web is of paramount importance for further progress in the area. Web Semantics: Cutting Edge and Future Directions in Healthcare describes the three major components of the study of Semantic Web, namely Representation, Reasoning, and Security with a special focus on the healthcare domain. This book summarizes the trends and current research advances in web semantics, emphasizing the existing tools and techniques, methodologies, and research solutions. It provides easily comprehensible information on Web Semantics including semantics for data and semantics for services.

Advances in Polymeric Nanomaterials for Biomedical Applications examines advanced polymer synthetic strategies for developing novel biomaterials for use in medicine. With a strong focus on fundamentals and structure, the authors also explore their fabrication, along with their current and potential biomedical applications. The book begins with a look at the fundamentals of polymeric nanomaterials and their properties and then discusses the design of biomaterials and their applications in drug delivery. Further chapters explore important applications, such as imaging and regenerative medicine, including current challenges and future trends. This valuable resource is especially useful for materials and polymer scientists, and bioengineers wishing to broaden their knowledge of polymeric nanobiomaterials.

This book coherently presents advances in design principles, processes, and methods in healthcare product design. It captures the implications of technological advances on designing healthcare products especially when market and societal needs pull each other in opposite directions. The contents focus on innovative design thinking processes and methods in developing healthcare products, applications of digital technologies in healthcare product design, amalgamation of artificial intelligence and design thinking for healthcare product design and quality, sustainability, and regulatory aspects in the design process. This book is a useful reference for those in the industry and academia.

The book Intelligent Healthcare: Infrastructure, Algorithms, and Management (R) cover a wide range of research topics on innovative intelligent healthcare solutions and advancements with the latest research developments. Data analytics are relevant for healthcare to meet many technical challenges and issues that need to be addressed to realize this potential. The advanced healthcare systems have to be upgraded with new capabilities such as data analytics, machine learning, intelligent decision making, and more professional services. The Internet of Things helps to design and develop intelligent healthcare solutions assisted by security, data analytics, and machine learning.This book will provide federated learning, Data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart healthcare. This book aims to attract works on multidisciplinary research spanning across computer science and engineering, environmental studies, services, urban planning and development, Healthcare, social sciences, and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative learning and computing solutions and big medical data-powered applications to cope with the real-world challenges for building smart healthcare sectors. Main Features: O Immersive technologies in healthcare O Internet of medical things O Federated learning algorithms O Explainable AI in Pervasive Healthcare O New management principles using biomedical data O Secured healthcare management systems This book aims to set up a better understanding of data scientists, researchers, and technologists under innovative digital health. The reader can find out existing research challenges, current market trends, and low-cost technologies to smoothly address the digital health issue.