Medical imaging now plays a major role in diagnosis, choice of therapy, and follow-up. However, patients are often intimidated by the multiple imaging modalities available, the indications for their use, the imposing equipment, what the examinations are like and how long they last, and the advantages and disadvantages of various procedures. This book is designed to provide explanations for these and other issues in order to relieve some of the anxiety related to medical imaging studies.

Titles in the Pocket Tutor series give practical guidance on subjects that medical students and foundation doctors need help with on the go, at a highly affordable price that puts them within reach of those rotating through modular courses or working on attachment. Topics reflect information needs stemming from today's integrated undergraduate & foundation courses: * Common investigations (ECG, imaging, etc) * Clinical skills (surface anatomy, patient examination, etc.) * Clinical specialties that students perceive as too small to merit a textbook (psychiatry, renal medicine) Key Points * Highly affordable price and convenient pocket size format - fits in back pocket * Logical, sequential content: the first principles of emergency imaging, then a guide to understanding a normal image and the building blocks of an abnormal image, before describing specific clinical disorders * Clinical disorders are illustrated by high quality radiographs, ultrasounds, CTs and MRIs, with brief accompanying text that clearly identifies the defining feature of the image * Focuses on the conditions that medical students and foundation doctors are most likely to see and be tested on

Recent advancements in the technology of medical imaging, such as CT and MRI scanners, are making it possible to create more detailed 3D and 4D images. These powerful images require vast amounts of digital data to help with the diagnosis of the patient. Artificial intelligence (AI) must play a vital role in supporting with the analysis of this medical imaging data, but it will only be viable as long as healthcare professionals and AI interact to embrace deep thinking platforms such as automation in the identification of diseases in patients. AI Innovation in Medical Imaging Diagnostics is an essential reference source that examines AI applications in medical imaging that can transform hospitals to become more efficient in the management of patient treatment plans through the production of faster imaging and the reduction of radiation dosages through the PET and SPECT imaging modalities. The book also explores how data clusters from these images can be translated into small data packages that can be accessed by healthcare departments to give a real-time insight into patient care and required interventions. Featuring research on topics such as assistive healthcare, cancer detection, and machine learning, this book is ideally designed for healthcare administrators, radiologists, data analysts, computer science professionals, medical imaging specialists, diagnosticians, medical professionals, researchers, and students.

Titles in the Pocket Tutor series give practical guidance on subjects that medical students and foundation doctors need help with ‘on the go’, at a highly-affordable price that puts them within reach of those rotating through modular courses or working on attachment.  Topics reflect information needs stemming from today’s integrated undergraduate and foundation courses: Common presentations Investigation options (e.g. ECG, imaging) Clinical and patient-orientated skills (e.g. examinations, history-taking) The highly-structured, bite-size content helps novices combat the ‘fear factor’ associated with day-to-day clinical training, and provides a detailed resource that students and junior doctors can carry in their pocket.   Key points New edition of the best-selling title that breaks down a complex and daunting subject using clearly-labelled, full-page ECG traces and concise but informative text Revised text and brand-new ECG traces bring the new edition fully up-to-date New chapters cover electrolyte and homeostatic disorders, and normal variants Logical, sequential content: relevant basic science, then a guide to understanding a normal ECG and the building blocks of an abnormal ECG, before describing clinical disorders

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.

In the medical field, there is a constant need to improve professionals' abilities to provide prompt and accurate diagnoses. The use of image and pattern recognizing software may provide support to medical professionals and enhance their abilities to properly identify medical issues. Medical Image Processing for Improved Clinical Diagnosis provides emerging research exploring the theoretical and practical aspects of computer-based imaging and applications within healthcare and medicine. Featuring coverage on a broad range of topics such as biomedical imaging, pattern recognition, and medical diagnosis, this book is ideally designed for medical practitioners, students, researchers, and others in the medical and engineering fields seeking current research on the use of images to enhance the accuracy of medical prognosis.

Biophotonic diagnostics/biomedical spectroscopy can revolutionise the medical environment by providing a responsive and objective diagnostic environment. This book aims to explain the fundamentals of the physical techniques used combined with the particular requirements of analysing medical/clinical samples as a resource for any interested party. In addition, it will show the potential of this field for the future of medical science and act as a driver for translation across many different biological problems/questions.

Neuroimaging, Part One, a text from The Handbook of Clinical Neurology illustrates how neuroimaging is rapidly expanding its reach and applications in clinical neurology. It is an ideal resource for anyone interested in the study of the nervous system, and is useful to both beginners in various related fields and to specialists who want to update or refresh their knowledge base on neuroimaging. This first volume specifically covers a description of imaging techniques used in the adult brain, aiming to bring a comprehensive view of the field of neuroimaging to a varying audience. It brings broad coverage of the topic using many color images to illustrate key points. Contributions from leading global experts are collated, providing the broadest view of neuroimaging as it currently stands. For a number of neurological disorders, imaging is not only critical for diagnosis, but also for monitoring the effect of therapies, and the entire field is moving from curing diseases to preventing them. Most of the information contained in this volume reflects the newness of this approach, pointing to this new horizon in the study of neurological disorders.

This book describes methods for statistical brain imaging data analysis from both the perspective of methodology and from the standpoint of application for software implementation in neuroscience research. These include those both commonly used (traditional established) and state of the art methods. The former is easier to do due to the availability of appropriate software. To understand the methods it is necessary to have some mathematical knowledge which is explained in the book with the help of figures and descriptions of the theory behind the software. In addition, the book includes numerical examples to guide readers on the working of existing popular software. The use of mathematics is reduced and simplified for non-experts using established methods, which also helps in avoiding mistakes in application and interpretation. Finally, the book enables the reader to understand and conceptualize the overall flow of brain imaging data analysis, particularly for statisticians and data-scientists unfamiliar with this area. The state of the art method described in the book has a multivariate approach developed by the authors' team. Since brain imaging data, generally, has a highly correlated and complex structure with large amounts of data, categorized into big data, the multivariate approach can be used as dimension reduction by following the application of statistical methods. The R package for most of the methods described is provided in the book. Understanding the background theory is helpful in implementing the software for original and creative applications and for an unbiased interpretation of the output. The book also explains new methods in a conceptual manner. These methodologies and packages are commonly applied in life science data analysis. Advanced methods to obtain novel insights are introduced, thereby encouraging the development of new methods and applications for research into medicine as a neuroscience.

This important volume is the first to address the use of neuroimaging in civil and criminal forensic contexts and to include discussion of prior precedents and court decisions. Equally useful for practicing psychiatrists and psychologists, it reviews both the legal and ethical consideraitons of neuroimaging.

Regular physical exercise is associated with substantial health benefits. Recent evidence not only holds for cardiovascular effects promoting "physical health," but also for the central nervous system believed to promote "brain health." Moderate physical exercise has been found to improve learning, memory, and attentional processing, with recent research indicating that neuroprotective mechanisms and associated plasticity in brain structure and function also benefit. Physical exercise is also known to induce a range of acute or sustained psychophysiological effects, among these mood elevation, stress reduction, anxiolysis, and hypoalgesia. Today, modern functional neuroimaging techniques afford direct measurement of the acute and chronic relation of physical exercise on the human brain, as well as the correlation of the derived physiological in vivo signals with behavioral outcomes recorded during and after exercise. A wide range of imaging techniques have been applied to human exercise research, ranging from electroencephalography (EEG), magnetoencephalography (MEG), near infrared spectroscopy (NIRS), magnetic resonance imaging (MRI) to positron emission tomography (PET). All of these imaging methods provide distinct information, and they differ considerably in terms of spatial and temporal resolution, availability, cost, and associated risks. However, from a "multimodal imaging" perspective, neuroimaging provides an unprecedented potential to unravel the neurobiology of human exercise, covering a wide spectrum ranging from structural plasticity in gray and white matter, network dynamics, global and regional perfusion, evoked neuronal responses to the quantification of neurotransmitter release. The aim of this book is to provide the current state of the human neuroimaging literature in the emerging field of the neurobiological exercise sciences and to outline future applications and directions of research.

This 6 volume set presents a groundbreaking resource in this branch of natural organic compounds and demonstrates how proton nuclear magnetic resonance (NMR) spectroscopy can be manipulated in structures of natural organic compounds. The authors provide the most comprehensive data of 17 kinds amounting to over 10,000 natural organic compounds. The 2nd volume mainly illustrates the molecular formula and structures of saponins.