While researchers with Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT) essentially addressed questions from the whole spectrum of cardiology, oncology, and the neurosciences, it was most notably the latter that provided completely new insights into physiological and disturbed human brain function. In Molecular Imaging in the Clinical Neurosciences, experts in the field provide the reader with up-to-date information on the basic principles of molecular imaging and its major applications in the clinical neurosciences. Beginning with a section offering a comprehensive review of the methodological foundations from physics, chemistry, and mathematics including mathematical modeling, essential for meaningful data analysis, this detailed volume then continues with sections on the major biological principles and neurochemical targets relevant in current neuroimaging research and the major clinical applications from the fields of psychiatry and neurology. Written for the popular Neuromethods series, this work contains the kind of key description and implementation advice that guarantees successful results. Authoritative and cutting-edge, Molecular Imaging in the Clinical Neurosciences serves as a helpful source of knowledge for both basic and clinical scientists from psychology, psychiatry, neurology, nuclear medicine, nuclear chemistry, and the associated disciplines, all of which makes molecular imaging such a rewarding, interdisciplinary field of work.

Most books discuss general and broad topics regarding molecular imagings. However, Ultrasmall Lanthanide Oxide Nanoparticles for Biomedical Imaging and Therapy, will mainly focus on lanthanide oxide nanoparticles for molecular imaging and therapeutics. Multi-modal imaging capabilities will discussed, along with up-converting FI by using lanthanide oxide nanoparticles. The synthesis will cover polyol synthesis of lanthanide oxide nanoparticles, Surface coatings with biocompatible and hydrophilic ligands will be discussed and TEM images and dynamic light scattering (DLS) patterns will be provided. Various techniques which are generally used in analyzing the synthesized surface coated nanoparticles will be explored and this section will also cover FT , IR analysis, XRD analysis, SQUID analysis, cytotoxicity measurements and proton relaxivity measurements. In vivo MR images, CT images, fluorescence images will be provided and Therapeutic application of gadolinium oxide nanoparticles will be discussed. Finally, future perpectives will be discussed. That is, present status and future works needed for clinical applications of lanthanide oxide nanoparticles to molecular imagings will be discussed.

The purpose of this monograph is both to introduce and review developed tomograhic methods for discovering 2D and 3D structures of the ionosphere and to discuss the experimental implementation of these methods. The theoretical part deals with the solution of the inverse problem of diffraction tomography for a wide range of properties of ionospheric media. Examples are given to illustrate the experimental reconstruction of electron-density distributions in ionospheric sections. In addition to addressing the specialist researcher, the detailed derivations and explanations make this book an excellent starting point for nonspecialists and graduate students who wish to enter this exciting new field to which the authors have made pioneering contributions.

This book chiefly addresses the analysis and design of geosynchronous synthetic aperture radar (GEO SAR) systems, focusing on the algorithms, analysis, methods used to compensate for ionospheric influences, and validation experiments for Global Navigation Satellite Systems (GNSS). Further, it investigates special problems in the GEO SAR context, such as curved trajectories, the Earth's rotation, the 'non-stop-and-go' model, high-order Doppler parameters, temporal-variant ionospheric errors etc. These studies can also be extended to SAR with very high resolution and long integration time. Given the breadth and depth of its coverage, scientists and engineers in SAR and advanced graduate students in related areas will greatly benefit from this book.

This book examines non-invasive, electrical-based methods for disease diagnosis and assessment of heart function. In particular, a formalized signal model is proposed since this offers several advantages over methods that rely on measured data alone. By using a formalized representation, the parameters of the signal model can be easily manipulated and/or modified, thus providing mechanisms that allow researchers to reproduce and control such signals. In addition, having such a formalized signal model makes it possible to develop computer tools that can be used for manipulating and understanding how signal changes result from various heart conditions, as well as for generating input signals for experimenting with and evaluating the performance of e.g. signal extraction methods. The work focuses on bioelectrical information, particularly electrical bio-impedance (EBI). Once the EBI has been measured, the corresponding signals have to be modelled for analysis. This requires a structured approach in order to move from real measured data to the model of the corresponding signals. This book proposes a generic framework for this procedure. It can be used as a guide for modelling impedance cardiography (ICG) and impedance respirography (IRG) signals, as well as for developing the corresponding bio-impedance signal simulator (BISS).

Traditional research methodologies in the human respiratory system have always been challenging due to their invasive nature. Recent advances in medical imaging and computational fluid dynamics (CFD) have accelerated this research. This book compiles and details recent advances in the modelling of the respiratory system for researchers, engineers, scientists, and health practitioners. It breaks down the complexities of this field and provides both students and scientists with an introduction and starting point to the physiology of the respiratory system, fluid dynamics and advanced CFD modeling tools. In addition to a brief introduction to the physics of the respiratory system and an overview of computational methods, the book contains best-practice guidelines for establishing high-quality computational models and simulations. Inspiration for new simulations can be gained through innovative case studies as well as hands-on practice using pre-made computational code. Last but not least, students and researchers are presented the latest biomedical research activities, and the computational visualizations will enhance their understanding of physiological functions of the respiratory system.

There have been many great advances in the field of biomedical imaging in recent years, with supramolecular chemistry playing a key role in the evolution of modern imaging techniques. Non-covalent supramolecular interactions are fundamental to countless biological processes, from host-guest binding to the stabilisation of complex structures. Supramolecular chemistry techniques can be employed to create probes that can be targeted to either exploit or disrupt these interactions, giving the potential for both diagnostic and therapeutic effects. Furthermore, in techniques such as contrast enhanced MRI, controlling the interactions between solvent molecules and the imaging agent is crucial to the development of the technique. With rapid growth in the synthesis and study of molecular imaging agents, the understanding of their associated techniques has sometimes lagged behind. Supramolecular Chemistry in Biomedical Imaging will fill this gap by clarifying the state of current understanding and the nature of the underlying problems inherent to addressing problems in biology. It will cover both the techniques used in imaging and the molecular and supramolecular systems used to exploit them. This publication targets academics coming to the field from mainstream supramolecular chemistry, research graduates and undergraduates interested in supramolecular chemistry, synthesis or imaging agents and imaging techniques for biomedical applications.

Are Amazon Alexa and Google Home limited to our bedrooms, or can they be used in hospitals? Do you envision a future where physicians work hand-in-hand with voice AI to revolutionize healthcare delivery? In the near future, clinical smart assistants will be able to automate many manual hospital tasks-and this will be only the beginning of the changes to come. Voice AI is the future of physician-machine interaction and this Focus book provides invaluable insight on its next frontier. It begins with a brief history and current implementations of voice-activated assistants and illustrates why clinical voice AI is at its inflection point. Next, it describes how the authors built the world's first smart surgical assistant using an off-the-shelf smart home device, outlining the implementation process in the operating room. From quantitative metrics to surgeons' feedback, the authors discuss the feasibility of this technology in the surgical setting. The book then provides an in-depth development guideline for engineers and clinicians desiring to develop their own smart surgical assistants. Lastly, the authors delve into their experiences in translating voice AI into the clinical setting and reflect on the challenges and merits of this pursuit. The world's first smart surgical assistant has not only reduced surgical time but eliminated major touch points in the operating room, resulting in positive, significant implications for patient outcomes and surgery costs. From clinicians eager for insight on the next digital health revolution to developers interested in building the next clinical voice AI, this book offers a guide for both audiences.

For over 50 years, coronary angiography has been the mainstay of diagnosing and quantifying the extent of coronary artery disease. However appreciation of the inherent limitations of conventional angiography has led to a plethora of new imaging modalities, each with their relative strengths and potential pitfalls. Advances in these techniques have given clinicians, as well as researchers, an overwhelming amount of information and the need for thoughtful interpretation. This outstanding book provides a comprehensive overview of the current status of imaging of coronary atherosclerosis. Covering the wide variety of available imaging modalities, the book provides state-of-the-art knowledge from leading authorities in each area. In their discussion, the authors include both invasive and non-invasive modalities, including the gold standard coronary angiography, the growing field of IVUS, and novel techniques such as functional imaging, molecular imaging, and the integration of biomarkers. The key concepts and practical information given in this volume will provide the reader with the necessary understanding to choosing appropriate imaging studies and building confidence in their skill set with each.

Apply all of the latest advances in imaging of the retina and posterior segment with Ryan's Retinal Imaging and Diagnostics. 12 chapters derived from the landmark reference Retina, 5th Edition offer the focused guidance you need to better understand, apply, and optimize new and emerging imaging technologies. "...recommended as an educational resource for retina fellowship trainees and retina specialists." Reviewed by Graefes Arch Clin Exp Ophthalmol, Nov 2014 Put the very latest diagnostic imaging methods to work in your practice, including optical coherence tomography (OCT), fluorescein angiography, indocyanine angiography, autofluorescence imaging, ophthalmic ultrasound, and more. Assess the effectiveness of the newest diagnostic technologies and approaches that are changing the management of retinal disease, including future imaging technologies which will soon become the standard. Benefit from the extensive knowledge and experience of esteemed editor and ophthalmologist, the late Dr. Stephen Ryan, as well as the truly global perspective of many other contributing world authorities.

Choice Recommended Title, April 2021 Bioimaging: Imaging by Light and Electromagnetics in Medicine and Biology explores new horizons in biomedical imaging and sensing technologies, from the molecular level to the human brain. It explores the most up-to-date information on new medical imaging techniques, such as the detection and imaging of cancer and brain diseases. This book also provides new tools for brain research and cognitive neurosciences based on new imaging techniques. Edited by Professor Shoogo Ueno, who has been leading the field of biomedical imaging for 40 years, it is an ideal reference book for graduate and undergraduate students and researchers in medicine and medical physics who are looking for an authoritative treatise on this expanding discipline of imaging and sensing in medicine and biology. Features: Provides step-by-step explanations of biochemical and physical principles in biomedical imaging Covers state-of-the art equipment and cutting-edge methodologies used in biomedical imaging Serves a broad spectrum of readers due to the interdisciplinary topic and approach Shoogo Ueno, Ph.D, is a professor emeritus of the University of Tokyo, Tokyo, Japan. His research interests include biomedical imaging and bioelectromagnetics, particularly in brain mapping and neuroimaging, transcranial magnetic stimulation (TMS), and magnetic resonance imaging (MRI). He was the President of the Bioelectromagnetics Society, BEMS (2003-2004) and the Chairman of the Commission K on Electromagnetics in Biology and Medicine of the International Union of Radio Science, URSI (2000-2003). He was named the IEEE Magnetics Society Distinguished Lecturer during 2010 and received the d'Arsonval Medal from the Bioelectromagnetics Society in 2010.

In the diagnosis and treatment of movement disorders, the use of neuroimaging has expanded widely and has been an exciting, important modality for unlocking the causes of abnormal motor control. With ever improving machinery, data collection techniques and analysis methods, researchers are now being presented with an exponentially increasing amount of data that they must wade through and interpret in the context of existing knowledge about movement disorders.

In "Neuroimaging in Movement Disorders, " the editors have produced a gold-standard resource that brings together an impressive international group of authorities in their respective fields to outline the current state of knowledge. Controversies, such as conflicting findings and methodological limitations, are covered and provide the reader with a comprehensive yet pragmatic understanding of the state of science. The chapters offer both comprehensive reviews of various neuroimaging methods and also more in-depth summaries of the contributions made by neuroimaging in individual movement disorders. Although many of the neuroimaging methods that are discussed have not been routinely used in clinical practice, the authors skillfully provide the reader with adequate detail to understand the requirements for using these methods and in some cases even the starting knowledge to begin local implementation. "Neuroimaging in Movement Disorders" is an indispensable reference that will be of value to all physicians and researchers involved in the care of patients with movement disorders.

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Stochastic Modeling for Medical Image Analysis provides a brief introduction to medical imaging, stochastic modeling, and model-guided image analysis. Today, image-guided computer-assisted diagnostics (CAD) faces two basic challenging problems. The first is the computationally feasible and accurate modeling of images from different modalities to obtain clinically useful information. The second is the accurate and fast inferring of meaningful and clinically valid CAD decisions and/or predictions on the basis of model-guided image analysis. To help address this, this book details original stochastic appearance and shape models with computationally feasible and efficient learning techniques for improving the performance of object detection, segmentation, alignment, and analysis in a number of important CAD applications. The book demonstrates accurate descriptions of visual appearances and shapes of the goal objects and their background to help solve a number of important and challenging CAD problems. The models focus on the first-order marginals of pixel/voxel-wise signals and second- or higher-order Markov-Gibbs random fields of these signals and/or labels of regions supporting the goal objects in the lattice. This valuable resource presents the latest state of the art in stochastic modeling for medical image analysis while incorporating fully tested experimental results throughout.

MRI in Practice continues to be the number one reference book and study guide for the registry review examination for MRI offered by the American Registry for Radiologic Technologists (ARRT). This latest edition offers in-depth chapters covering all core areas, including: basic principles, image weighting and contrast, spin and gradient echo pulse sequences, spatial encoding, k-space, protocol optimization, artefacts, instrumentation, and MRI safety. The leading MRI reference book and study guide. Now with a greater focus on the physics behind MRI. Offers, for the first time, equations and their explanations and scan tips. Brand new chapters on MRI equipment, vascular imaging and safety. Presented in full color, with additional illustrations and high-quality MRI images to aid understanding. Includes refined, updated and expanded content throughout, along with more learning tips and practical applications. Features a new glossary. MRI in Practice is an important text for radiographers, technologists, radiology residents, radiologists, and other students and professionals working within imaging, including medical physicists and nurses.

Choice Recommended Title, January 2021 This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-par performance with clinical experts. In the last section, the book offers a view on the complexity of the validation of artificial intelligence applications for commercial use, describing the recently introduced concept of software as a medical device, as well as good practices and relevant considerations for training and testing machine learning systems for medical use. Open problematics on the validation for public use of systems which by nature continuously evolve through new data is also explored. The book will be of interest to graduate students in medical physics, biomedical engineering and computer science, in addition to researchers and medical professionals operating in the medical imaging domain, who wish to better understand these technologies and the future of the field. Features: An accessible yet detailed overview of the field Explores a hot and growing topic Provides an interdisciplinary perspective

Computational methodologies of signal processing and imaging analysis, namely considering 2D and 3D images, are commonly used in different applications of the human society. For example, Computational Vision systems are progressively used for surveillance tasks, traf?c analysis, recognition process, inspection p- poses, human-machine interfaces, 3D vision and deformation analysis. One of the main characteristics of the Computational Vision domain is its int- multidisciplinary. In fact, in this domain, methodologies of several more fundam- tal sciences, such as Informatics, Mathematics, Statistics, Psychology, Mechanics and Physics are usually used. Besides this inter-multidisciplinary characteristic, one of the main reasons that contributes for the continually effort done in this domain of the human knowledge is the number of applications in the medical area. For instance, it is possible to consider the use of statistical or physical procedures on medical images in order to model the represented structures. This modeling can have different goals, for example: shape reconstruction, segmentation, registration, behavior interpretation and simulation, motion and deformation analysis, virtual reality, computer-assisted therapy or tissue characterization. The main objective of the ECCOMAS Thematic Conferences on Computational Vision and Medical Image Processing (VIPimage) is to promote a comprehensive forum for discussion on the recent advances in the related ?elds trying to id- tify widespread areas of potential collaboration between researchers of different sciences.

Designed to provide those engaged in modern medical imaging with a coherent perspective of the entire discipline so that one protocol is no longer an isolated or independent mode of imaging from others, to wit: single photon emission computed tomography (SPECT), positron emission tomography (PET) or magnetic resonance imaging (MRI). Introduces biomagnetic imaging as a third new modality.

Covers different modalities for improvement of healthcare system Describes implementation strategies and their applications in diagnosis of modalities Reviews automatic identification of related disorders using medical modality Discusses bio-potential signals and their appropriate analysis for studying different disorders Includes case studies, real-time examples and research directions

Advances in digital technology led to the development of digital x-ray detectors that are currently in wide use for projection radiography, including Computed Radiography (CR) and Digital Radiography (DR). Digital Imaging Systems for Plain Radiography addresses the current technological methods available to medical imaging professionals to ensure the optimization of the radiological process concerning image quality and reduction of patient exposure. Based on extensive research by the authors and reference to the current literature, the book addresses how exposure parameters influence the diagnostic quality in digital systems, what the current acceptable radiation doses are for useful diagnostic images, and at what level the dose could be reduced to maintain an accurate diagnosis. The book is a valuable resource for both students learning the field and for imaging professionals to apply to their own practice while performing radiological examinations with digital systems.

Advanced Imaging of the Abdomen is invaluable to the practising radiologist, and the more senior radiology resident and fellow, who is looking for a background reference source when discussing a suggested imaging approach with the referring physician.

The book includes extensive lists, tables, line drawings and illustrations - ultrasonography, computed tomography, magnetic resonance images, scintigraphy. It bridges the interface between the referring clinician and radiologist when faced with a patient suspected of having a complex or more unusual abdominal condition.

This book examines the use of biomedical signal processing-EEG, EMG, and ECG-in analyzing and diagnosing various medical conditions, particularly diseases related to the heart and brain. In combination with machine learning tools and other optimization methods, the analysis of biomedical signals greatly benefits the healthcare sector by improving patient outcomes through early, reliable detection. The discussion of these modalities promotes better understanding, analysis, and application of biomedical signal processing for specific diseases. The major highlights of Biomedical Signal Processing for Healthcare Applications include biomedical signals, acquisition of signals, pre-processing and analysis, post-processing and classification of the signals, and application of analysis and classification for the diagnosis of brain- and heart-related diseases. Emphasis is given to brain and heart signals because incomplete interpretations are made by physicians of these aspects in several situations, and these partial interpretations lead to major complications. FEATURES Examines modeling and acquisition of biomedical signals of different disorders Discusses CAD-based analysis of diagnosis useful for healthcare Includes all important modalities of biomedical signals, such as EEG, EMG, MEG, ECG, and PCG Includes case studies and research directions, including novel approaches used in advanced healthcare systems This book can be used by a wide range of users, including students, research scholars, faculty, and practitioners in the field of biomedical engineering and medical image analysis and diagnosis.

There is an urgent need to develop and integrate new statistical, mathematical, visualization, and computational models with the ability to analyze Big Data in order to retrieve useful information to aid clinicians in accurately diagnosing and treating patients. The main focus of this book is to review and summarize state-of-the-art big data and deep learning approaches to analyze and integrate multiple data types for the creation of a decision matrix to aid clinicians in the early diagnosis and identification of high risk patients for human diseases and disorders. Leading researchers will contribute original research book chapters analyzing efforts to solve these important problems.

This book explores novel methods for implementing X-ray diffraction technology as an imaging modality, which have been made possible through recent breakthroughs in detector technology, computational power, and data processing algorithms. The ability to perform fast, spatially-resolved X-ray diffraction throughout the volume of a sample opens up entirely new possibilities in areas such as material analysis, cancer diagnosis, and explosive detection, thus offering the potential to revolutionize the fields of medical, security, and industrial imaging and detection. Featuring chapters written by an international selection of authors from both academia and industry, the book provides a comprehensive discussion of the underlying physics, architectures, and applications of X-ray diffraction imaging that is accessible and relevant to neophytes and experts alike. Teaches novel methods for X-ray diffraction imaging Comprehensive and self-contained discussion of the relevant physics, imaging techniques, system components, and data processing algorithms Features state-of-the-art work of international authors from both academia and industry. Includes practical applications in the medical, industrial, and security sectors