Synchrotron radiation has been a revolutionary and invaluable research tool for a wide range of scientists, including chemists, biologists, physicists, materials scientists, geophysicists. It has also found multidisciplinary applications with problems ranging from archeology through cultural heritage to paleontology. The subject of this book is x-ray spectroscopy using synchrotron radiation, and the target audience is both current and potential users of synchrotron facilities. The first half of the book introduces readers to the fundamentals of storage ring operations, the qualities of the synchrotron radiation produced, the x-ray optics required to transport this radiation, and the detectors used for measurements. The second half of the book describes the important spectroscopic techniques that use synchrotron x-rays, including chapters on x-ray absorption, x-ray fluorescence, resonant and non-resonant inelastic x-ray scattering, nuclear spectroscopies, and x-ray photoemission. A final chapter surveys the exciting developments of free electron laser sources, which promise a second revolution in x-ray science. Thanks to the detailed descriptions in the book, prospective users will be able to quickly begin working with these techniques. Experienced users will find useful summaries, key equations, and exhaustive references to key papers in the field, as well as outlines of the historical developments in the field. Along with plentiful illustrations, this work includes access to supplemental Mathematica notebooks, which can be used for some of the more complex calculations and as a teaching aid. This book should appeal to graduate students, postdoctoral researchers, and senior scientists alike.

The rise in living standards increases the expectation of people in almost every field. At the forefront is health. Over the past few centuries, there have been major developments in healthcare. Medical device technology and developments in artificial intelligence (AI) are among the most important ones. The improving technology and our ability to harness the technology effectively by means such as AI have led to unprecedented advances, resulting in early diagnosis of diseases. AI algorithms enable the fast and early evaluation of images from medical devices to maximize the benefits. While developments in the field of AI were quickly adapted to the field of health, in some cases this contributed to the formation of innovative artificial intelligence algorithms. Today, the most effective artificial intelligence method is accepted as deep learning. Convolutional neural network (CNN) architectures are deep learning algorithms used for image processing. This book contains applications of CNN methods. The content is quite extensive, including the application of different CNN methods to various medical image processing problems. Readers will be able to analyze the effects of CNN methods presented in the book in medical applications.

Automatic detection and segmentation of anatomical structures in medical images are prerequisites to subsequent image measurements and disease quantification, and therefore have multiple clinical applications. This book presents an efficient object detection and segmentation framework, called Marginal Space Learning, which runs at a sub-second speed on a current desktop computer, faster than the state-of-the-art. Trained with a sufficient number of data sets, Marginal Space Learning is also robust under imaging artifacts, noise and anatomical variations. The book showcases 35 clinical applications of Marginal Space Learning and its extensions to detecting and segmenting various anatomical structures, such as the heart, liver, lymph nodes and prostate in major medical imaging modalities (CT, MRI, X-Ray and Ultrasound), demonstrating its efficiency and robustness.

This is an introduction to recent developments in the application of wave-splitting methods to direct and inverse scattering of wave fields. Here wave-splitting refers to the decomposition of the total field into two components which propagate in opposite directions. Although the text emphasizes time domain methods, it includes some applications to frequency domain problems.

Ultrasound imaging technology has experienced a dramatic change in the last 30 years. Because of its non-invasive nature and continuing improvements in image quality, ultrasound imaging is progressively achieving an important role in the assessment and characterization of cardiovascular imaging. Speckle is inherent in ultrasound imaging giving rise to a granular appearance instead of homogeneous, flat shades of gray, as is visible and as such, speckle can severely compromise interpretation of ultrasound images, particularly in discrimination of small structures. On the other hand, speckle can be used in the detection of time varying phenomena, or tracking tissue motion. The objective of this book is to provide a reference edited volume covering the whole spectrum of speckle phenomena, theoretical background and modelling, algorithms and selected applications in cardiovascular ultrasound imaging and video processing and analysis. The book is organized under the following four parts, Part I: Introduction to Speckle Noise; Part II: Speckle Filtering; Part III: Speckle Tracking; Part IV: Selected Applications in Cardiovascular Imaging.

This text emphasizes the importance of artificial intelligence techniques in the field of biological computation. It also discusses fundamental principles that can be applied beyond bio-inspired computing. It comprehensively covers important topics including data integration, data mining, machine learning, genetic algorithms, evolutionary computation, evolved neural networks, nature-inspired algorithms, and protein structure alignment. The text covers the application of evolutionary computations for fractal visualization of sequence data, artificial intelligence, and automatic image interpretation in modern biological systems. The text is primarily written for graduate students and academic researchers in areas of electrical engineering, electronics engineering, computer engineering, and computational biology. This book: * Covers algorithms in the fields of artificial intelligence, and machine learning useful in biological data analysis. * Discusses comprehensively artificial intelligence and automatic image interpretation in modern biological systems. * Presents the application of evolutionary computations for fractal visualization of sequence data. * Explores the use of genetic algorithms for pair-wise and multiple sequence alignments. * Examines the roles of efficient computational techniques in biology.

Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis.

"Molecular Imaging: Fundamentals and Applications" is a comprehensive monograph which describes not only the theory of the underlying algorithms and key technologies but also introduces a prototype system and its applications, bringing together theory, technology and applications. By explaining the basic concepts and principles of molecular imaging, imaging techniques, as well as research and applications in detail, the book provides both detailed theoretical background information and technical methods for researchers working in medical imaging and the life sciences. Clinical doctors and graduate students will also benefit from this book. Jie Tian is a professor at the Institute of Automation, Chinese Academy of Sciences, China.

Focal therapy is a promising option for selected patients who have localized low or intermediate-risk prostate cancer, providing a compelling alternative between active surveillance and radical therapies by targeting the index lesion and preserving as much tissue as possible. Numerous cohort studies have already investigated multiple focal techniques, such as cryotherapy, high-intensity focused ultrasound, brachytherapy, photodynamic therapy, laser therapy, irreversible electroporation and cyberknife methods, all of which have demonstrated positive oncological outcomes with 70 to 90 % negative follow-up biopsy. These various ablative techniques have produced only minor side-effects concerning urinary function, a low rate of erectile dysfunction, and have demonstrated a limited rectal toxicity. As a result, the primary end-point has now shifted and a new strategy needs to be established for patient follow-up and for defining treatment failure. Written by international experts in the field, this book is mainly focused on new techniques, all of which are amply illustrated. Technical Aspects of Focal Therapy in Localized Prostate Cancer will be of great practical value to all urologists and oncologists.

Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.

Retrograde Ureteroscopy: Handbook of Endourology contains five focused, review-oriented volumes that are ideal for students and clinicians looking for a comprehensive review rather than a whole course. Each volume is easily accessible through eBook format. Topics covered review both the endourological diagnosis and treatment of prostate, urethral, urinary bladder, upper urinary tract, and renal pathology, with all chapters describing the most recent techniques, reviewing the latest results, and analyzing the most modern technologies. In the past ten years, the field of endourology has expanded beyond the urinary tract to include all urologic, minimally-invasive surgical procedures. Recent advancements in robotic and laparoscopic bladder surgery make this one of the fastest moving fields in medicine. As current textbooks are too time-consuming for busy urologists or trainees who also need to learn other areas of urology, this collection provides a quick references with over 4000 images that are appropriate for fellows and those teaching in the field.

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.

Now a routine tool in biomedical and life science research, live cell imaging has made major progress enabling this core biochemical, cell, and molecular biology technique to become even more powerful, versatile, and affordable. In Live Cell Imaging: Methods and Protocols, a panel of expert contributors provide a comprehensive compendium of experimental approaches to live cell imaging in the form of several overview chapters followed by representative examples and case studies covering different aspects of the most current methodology. By examining a range of state-of-the-art protocols extensively validated in complex biological studies, this volume highlights new experimental and instrumental opportunities and helps researchers to select appropriate imaging methods for their specific biological questions and measurement tasks. Written in the highly successful Methods in Molecular BiologyT series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Live Cell Imaging: Methods and Protocols promises to contribute greatly to the further development and dissemination of this fundamentally important technology which spans across many disciplines including molecular and cell biology, chemistry, physics, optics, engineering, cell physiology, and medicine. Written for: Molecular and cellular biologists, chemists, physicists, optics specialists, engineers, cell physiologists, and medical doctors

This book covers the most recent advances in using nanoparticles for biomedical imaging, including magnetic resonance imaging (MRI), magnetic particle imaging (MPI), nuclear medicine, ultrasound (US) imaging, computed tomography (CT), and optical imaging. Topics include nanoparticles for MRI and MPI, siRNA delivery, theranostic nanoparticles for PET imaging of drug delivery, US nanoparticles for imaging drug delivery, inorganic nanoparticles for targeted CT imaging, and quantum dots for optical imaging. This book serves as a valuable resource for the fundamental science of diagnostic nanoparticles and their interactions with biological targets, providing a practical handbook for improved detection of disease and its clinical implementation.

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.

The application of optical methods for investigating neocortical circuit dynamics has greatly expanded in recent years, providing novel insights into the fascinating world of brain function. Optical Imaging of Neocortical Dynamics presents a guide to these indispensible tools, which cover a broad range of spatiotemporal scales and a large variety of signaling aspects, ranging from voltage changes to metabolic states. This detailed volume specifically explores methods that are applied in experiments on living brains (in vivo) and that relate to functional properties on the spatial scale of cortical circuits. Beginning with an introductory section that focuses on physical fundamentals of optical imaging as well as molecular tools used for in vivo optical imaging and optogenetic control, the book continues with the most relevant methods and their applications to investigate changes in neuronal and glial activity states as well as optical imaging methods probing metabolic states. Written for the Neuromethods series, this volume contains the kind of detail and key implementation advice that ensures successful results in the lab. Practical and easy to use, Optical Imaging of Neocortical Dynamics serves as an ideal guide for researchers who aim to apply these highly valuable tools to their own neuroscientific studies.

This book explains in detail the potential value of the hybrid modalities, SPECT-CT and PET-CT, in the imaging of cardiac innervation in a wide range of conditions and diseases, including ischemic heart disease, diabetes mellitus, heart failure, amyloidosis, heart transplantation, and ventricular arrhythmias. Imaging of the brain-heart axis in neurodegenerative disease and stress and of cardiotoxicity is also discussed. The roles of the various available tracers are fully considered, and individual chapters address radiopharmaceutical development under GMP, imaging physics, and kinetic modeling software. Highly relevant background information is included on the autonomic nervous system of the heart and its pathophysiology, and in addition future perspectives are discussed. Awareness of the importance of autonomic innervation of the heart for the optimal management of cardiac patients is growing, and there is an evident need for objective measurement techniques or imaging modalities. In this context, Autonomic Innervation of the Heart will be of wide interest to clinicians, researchers, and industry.

The critical care unit is an intense clinical environment with huge responsibilities on the professionals caring for these patients. Imaging is a key source of diagnostic information, but the conditions in which diagnostic imaging has to be performed are often extremely challenging and significantly different to imaging in the non acute setting. Imaging the ICU Patient reviews imaging procedures on the ICU in a highly practical and memorable manner. Swift and efficient clinical decision-making is rewarded on the ICU and this book serves as a practical handbook.

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.

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).

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.

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.