Mastery of ECG interpretation is achieved not only by pattern recognition, but equally importantly, by a clear, practical understanding of how electricity moves through the heart and how disruption of that movement manifests itself via ECG tracings. ECGs for Beginners, written by one of the world's most respected electrophysiologists with over 40 years experience of training clinicians, will provide cardiology and electrophysiology trainees with an easy to follow, step-by-step guide to the topic, thus enabling them to both understand and interpret ECG readings in order to to best manage their patients.Packed with over 250 high-quality ECG tracings, as well as management algorithms and key points throughout, every chapter also contains self-assessment questions, allowing the reader to test themselves on what they've just learnt. All kinds of arrhythmias will be covered, as well as morphological abnormalities such as atrial and ventricular problems. Importantly, normal ECG readings will be presented alongside abnormal readings, to best demonstrate how and why abnormalities occur.ECGs for Beginners is an essential purchase for all cardiology and electrophysiology trainees, as well as being a handy refresher guide for the experienced physician.

The Oxford Handbook of Functional Brain Imaging in Neuropsychology and Cognitive Neurosciences describes in a readily accessible manner the several functional neuroimaging methods and critically appraises their applications that today account for a large part of the contemporary cognitive neuroscience and neuropsychology literature. The complexity and the novelty of these methods often cloud appreciation of the methods' contributions and future promise. The Handbook begins with an overview of the basic concepts of functional brain imaging common to all methods, and proceeds with a description of each of them, namely magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), positron emission tomography (PET), diffusion tensor imaging (DTI), and transcranial magnetic stimulation (TMS). Its second part covers the various research applications of functional neuroimaging on issues like the function of the default mode network; the possibility and the utility of imaging of consciousness; the search for mnemonic traces of concepts; human will and decision-making; motor cognition; language; the mechanisms of affective states and pain; the presurgical mapping of the brain; and others. As such, the volume reviews the methods and their contributions to current research and comments on the degree to which they have enhanced our understanding of the relation between neurophysiological activity and sensory, motor, and cognitive functions. Moreover, it carefully considers realistic contributions of functional neuroimaging to future endeavors in cognitive neuroscience, medicine, and neuropsychology.

Diagnostic Imaging will help medical students, junior doctors, residents and trainee radiologists understand the principles behind interpreting all forms of imaging. Providing a balanced account of all the imaging modalities available including plain film, ultrasound, computed tomography, magnetic resonance imaging, radionuclide imaging and interventional radiology it explains the techniques used and the indications for their use. Organised by body system, it covers all anatomical regions. In each region the authors discuss the most suitable imaging technique and provide guidelines for interpretation, illustrating clinical problems with normal and abnormal images. Diagnostic Imaging is extensively illustrated throughout, featuring high quality full-colour images and more than 600 photographs. The images are downloadable in PowerPoint format from the brand new companion website at www.wileydiagnosticimaging.com, which also has over 100 interactive MCQs, to aid learning and teaching. When you purchase the book you also receive access to the Wiley E-Text: Powered by VitalSource. This is an interactive digital version of the book, featuring downloadable text and images, highlighting and note-taking facilities, bookmarking, cross-referencing, in-text searching, and linking to references and abbreviations. Diagnostic Imaging is also available on CourseSmart, offering extra functionality as well as an immediate way to access the book. For more details, see www.coursesmart.com or The Anytime, Anywhere Textbook section.

Epilepsy is a prevalent and serious neurological disorder. This vital textbook addresses the role of neuroimaging as a unique tool to provide in vivo biomarkers aimed at furthering our understanding of causes and consequences of epilepsy in a day-to-day clinical context. Unique in its approach, this translational book presents a critical appraisal of advanced pre-clinical biomarkers that allows capturing epileptogenesis at molecular, cellular, and neuronal system levels. The book is divided into four sections. Part I includes a series of chapters focused on imaging of early disease stages. Part II discusses lesion detection and network analysis methods. Part III focuses on imaging methods used to predict response to antiepileptic drugs and surgery. Finally, Part IV presents imaging techniques used to evaluate disease consequence.

Deep Learning for Chest Radiographs enumerates different strategies implemented by the authors for designing an efficient convolution neural network-based computer-aided classification (CAC) system for binary classification of chest radiographs into "Normal" and "Pneumonia." Pneumonia is an infectious disease mostly caused by a bacteria or a virus. The prime targets of this infectious disease are children below the age of 5 and adults above the age of 65, mostly due to their poor immunity and lower rates of recovery. Globally, pneumonia has prevalent footprints and kills more children as compared to any other immunity-based disease, causing up to 15% of child deaths per year, especially in developing countries. Out of all the available imaging modalities, such as computed tomography, radiography or X-ray, magnetic resonance imaging, ultrasound, and so on, chest radiographs are most widely used for differential diagnosis between Normal and Pneumonia. In the CAC system designs implemented in this book, a total of 200 chest radiograph images consisting of 100 Normal images and 100 Pneumonia images have been used. These chest radiographs are augmented using geometric transformations, such as rotation, translation, and flipping, to increase the size of the dataset for efficient training of the Convolutional Neural Networks (CNNs). A total of 12 experiments were conducted for the binary classification of chest radiographs into Normal and Pneumonia. It also includes in-depth implementation strategies of exhaustive experimentation carried out using transfer learning-based approaches with decision fusion, deep feature extraction, feature selection, feature dimensionality reduction, and machine learning-based classifiers for implementation of end-to-end CNN-based CAC system designs, lightweight CNN-based CAC system designs, and hybrid CAC system designs for chest radiographs. This book is a valuable resource for academicians, researchers, clinicians, postgraduate and graduate students in medical imaging, CAC, computer-aided diagnosis, computer science and engineering, electrical and electronics engineering, biomedical engineering, bioinformatics, bioengineering, and professionals from the IT industry.

Image-Based Computational Modeling of the Human Circulatory and Pulmonary Systems provides an overview of the current modeling methods and applications enhancing interventional treatments and computer-aided surgery. A detailed description of the techniques behind image acquisition, processing and three-dimensional reconstruction are included. Techniques for the computational simulation of solid and fluid mechanics and structure interaction are also discussed, in addition to various cardiovascular and pulmonary applications. Engineers and researchers involved with image processing and computational modeling of human organ systems will find this a valuable reference.

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 book discusses the impact of machine learning and computational intelligent algorithms on medical image data processing, and introduces the latest trends in machine learning technologies and computational intelligence for intelligent medical image analysis. The topics covered include automated region of interest detection of magnetic resonance images based on center of gravity; brain tumor detection through low-level features detection; automatic MRI image segmentation for brain tumor detection using the multi-level sigmoid activation function; and computer-aided detection of mammographic lesions using convolutional neural networks.

A complete and practical guide, this text describes how to produce high-quality radiographic and ultrasound images. The first half of the book covers equipment, safety, and technique - all major responsibilities of the veterinary technician. The second half details radiographic positioning for small animals, large animals, and exotics. Reflecting the major role of ultrasonography in veterinary practice, the book concludes with an expanded chapter on diagnostic ultrasound. Practical, concise clinical format Written at the appropriate reading level for technicians Abundant illustrations emphasize basic radiographic and ultrasonographic principles, techniques, and equipment used in veterinary practice Concise and understandable discussion of physics and radiography Examples of common artifacts show how to avoid misinterpretation of imaging studies Excellent coverage of radiation safety Practical technique charts Excellent coverage of small- and large-animal positioning Exotics chapter featuring rodents (including ferrets), reptiles, and birds Ultrasound chapter that includes normal ultrasonographic findings, along with corresponding images Helpful hints given for obtaining quality images and avoiding common pitfalls reflect the authors' experiences at a busy teaching institution New cardiac ultrasound scanning techniques with 20 new ultrasound images New images of the latest x-ray equipment Updated pedagogical features, including outlines, key points, chapter objectives, and helpful hints for veterinary technicians

The Comatose Patient, Second Edition, is a critical historical overview of the concepts of consciousness and unconsciousness, covering all aspects of coma within 100 detailed case vignettes. This comprehensive text includes principles of neurologic examination of comatose patients as well as instruction of the FOUR Score coma scale, and also discusses landmark legal cases and ethical problems. As the Chair of Division of Critical Care Neurology at Mayo Clinic, Dr. Wijdicks uses his extensive knowledge to discuss a new practical multistep approach to the diagnosis of the comatose patient. Additionally, this edition includes extensive coverage of the interpretation of neuroimaging and its role in daily practice and decision making, as well as management in the emergency room and ICU. Dr. Wijdicks details long-term supportive care and an appropriate approach to communication with family members about end-of-life decision making.

Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs.

The third edition of Carvers' Medical Imaging supports radiography students to take a reflective, evidence-based approach that will enhance their practice. This important textbook comprehensively covers the full range of medical imaging methods and techniques in one volume, and discusses them in relation to imaging principles, radiation dose, patient condition, body area and pathologies. It encourages the student to critically analyse their work rather than simply carrying out tasks. The book has been updated by an impressive team of contributors to align with developments in both radiographic techniques and the role of the radiographer. It is an essential companion for students of BSc (Hons) diagnostic radiography, those undertaking a foundation degree in radiographic practice or bachelor of medicine, and postgraduates alike. Comprehensive, fully illustrated and well referenced discussion of all imaging techniques. Full image evaluation for radiographic examinations, including common errors New material on potential impact of errors on accuracy of the radiographic report New sections on preliminary clinical evaluation for projection radiography examinations, which prepares students for UK professional standards Section on cross infection implications (relevant post COVID-19) Includes imaging of children with suspected physical abuse

Addressing the basic concepts of radiological physics and radiation protection, together with a structured approach to image interpretation, Radiology at a Glance is the perfect guide for medical students, junior doctors and radiologists. Covering the radiology of plain films, fluoroscopy, CT, MRI, intervention, nuclear medicine, and mammography, this edition has been fully updated to reflect advances in the field and now contains new spreads on cardiac, breast and bowel imaging, as well as further information on interventional radiology. Radiology at a Glance: * Assumes no prior knowledge of radiology * Addresses both theory and clinical practice through theoretical and case-based chapters * Provides structured help in assessing which radiological procedures are most appropriate for specific clinical problems * Includes increased image clarity Supported by 'classic cases' chapters in each section, and presented in a clear and concise format, Radiology at a Glance is easily accessible whether on the ward or as a quick revision guide.

Covering the entire spectrum of this fast-changing field, Diagnostic Imaging: Obstetrics, fourth edition, is an invaluable resource for radiologists, perinatologists, and trainees-anyone who requires an easily accessible, highly visual reference on today's obstetric imaging. Dr. Paula J. Woodward and a team of highly regarded experts provide up-to-date information on recent advances in technology and the understanding of fetal development and disease processes to help you make informed decisions at the point of care. The text is lavishly illustrated, delineated, and referenced, making it a useful learning tool as well as a handy reference for daily practice. Serves as a one-stop resource for key concepts and information on obstetric imaging, including a wealth of new material and content updates throughout Features more than 3,000 illustrations (grayscale, 3D, color, and pulsed-wave Doppler ultrasound; fetal MR; extensive clinical and/or pathologic correlation; and full-color illustrations) 1,300 additional digital images, and 175 new ultrasound video clips Features updates from cover to cover including new information on the genetic basis of fetal diseases, as well as new diagnoses and management protocols; additional and expanded differential diagnoses; and recent consensus guidelines and practice standards Covers dramatic new changes in technology, including recent innovations in 3D ultrasound and fetal MRI, as well as the earliest ultrasound findings seen with each condition due to improved ultrasound technology Reflects a multidisciplinary, collaborative approach to diagnosis, management, and treatment between radiologists, perinatologists, pediatricians, and surgeons Includes embryology and anatomy overview chapters, along with pertinent differential diagnoses for comprehensive coverage Uses bulleted, succinct text and highly templated chapters for quick comprehension of essential information at the point of care Enhanced eBook version included with purchase. Your enhanced eBook allows you to access all of the text, figures, and references from the book on a variety of devices

Computational Retinal Image Analysis: Tools, Applications and Perspectives gives an overview of contemporary retinal image analysis (RIA) in the context of healthcare informatics and artificial intelligence. Specifically, it provides a history of the field, the clinical motivation for RIA, technical foundations (image acquisition modalities, instruments), computational techniques for essential operations, lesion detection (e.g. optic disc in glaucoma, microaneurysms in diabetes) and validation, as well as insights into current investigations drawing from artificial intelligence and big data. This comprehensive reference is ideal for researchers and graduate students in retinal image analysis, computational ophthalmology, artificial intelligence, biomedical engineering, health informatics, and more.

Handbook of Medical Image Computing and Computer Assisted Intervention presents important advanced methods and state-of-the art research in medical image computing and computer assisted intervention, providing a comprehensive reference on current technical approaches and solutions, while also offering proven algorithms for a variety of essential medical imaging applications. This book is written primarily for university researchers, graduate students and professional practitioners (assuming an elementary level of linear algebra, probability and statistics, and signal processing) working on medical image computing and computer assisted intervention.

Measurement of solid tumor response to treatment relies mainly on imaging. WHO tumor response criteria and, more recently, RECIST (response evaluation criteria in solid tumors) have provided means to objectively measure tumor response in clinical trials with imaging. These guidelines have been rapidly adopted in clinical practice to monitor patient treatment and for therapy planning. However, relying only on anatomical information is not always sufficient when evaluating new drugs that will reduce a tumor's functionality while preserving its size. Finding more reliable and reproducible measures of tumor response is one of the most important and difficult challenges facing modern radiology as it requires an entirely new approach to imaging. The aim of this book is to address the assessment of response to treatment by adopting a multidisciplinary perspective, just as occurs in real life in a comprehensive cancer center. Oncologists and imaging experts consider two cancer models, locally advanced disease and metastatic disease, jointly exploring both conventional and advanced means of measuring response to standard treatment protocols and new targeted therapies.

This book presents fundamental requirements, electrical specification, and parameter tradeoffs of wearable EEG acquisition circuits, especially those compatible with dry electrodes for user-friendly recordings. The authors introduce active electrode, the most promising solution for dry electrodes-based EEG measurement. This architectural concept has been combined with various, innovative circuit design techniques to illustrate structured IC design methodologies for high performance EEG recording. This book also gives examples on the design, implementation and evaluation of three generations of active electrode ICs.

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).

This book constitutes the refereed joint proceedings of the First International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2018, the First International Workshop on Deep Learning Fails, DLF 2018, and the First International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 4 full MLCN papers, the 6 full DLF papers, and the 6 full iMIMIC papers included in this volume were carefully reviewed and selected. The MLCN contributions develop state-of-the-art machine learning methods such as spatio-temporal Gaussian process analysis, stochastic variational inference, and deep learning for applications in Alzheimer's disease diagnosis and multi-site neuroimaging data analysis; the DLF papers evaluate the strengths and weaknesses of DL and identify the main challenges in the current state of the art and future directions; the iMIMIC papers cover a large range of topics in the field of interpretability of machine learning in the context of medical image analysis.

This book constitutes the proceedings of the Workshop on Shape in Medical Imaging, ShapeMI 2018, held in conjunction with the 21st International Conference on Medical Image Computing, MICCAI 2018, in Granada, Spain, in September 2018. The 26 full papers and 2 short papers presented were carefully reviewed and selected for inclusion in this volume. The papers discuss novel approaches and applications in shape and geometry processing and their use in research and clinical studies and explore novel, cutting-edge theoretical methods and their usefulness for medical applications, e.g., from the fields of geometric learning or spectral shape analysis.