Nuclear chemistry represents a vital field of basic and applied research. In the 1st volume an introduction to the field is given including relevant parameters, modes of radioactivity, detection methods, and more. In the 2nd volume, modern applications are covered including analytical technologies, pharmaceutical and medical applications, and nuclear energy. The new editions have updated literature references and new material throughout.

Image processing is a hands-on discipline, and the best way to learn is by doing. This text takes its motivation from medical applications and uses real medical images and situations to illustrate and clarify concepts and to build intuition, insight and understanding. Designed for advanced undergraduates and graduate students who will become end-users of digital image processing, it covers the basics of the major clinical imaging modalities, explaining how the images are produced and acquired. It then presents the standard image processing operations, focusing on practical issues and problem solving. Crucially, the book explains when and why particular operations are done, and practical computer-based activities show how these operations affect real images. All images, links to the public-domain software ImageJ and custom plug-ins, and selected solutions are available from www.cambridge.org/books/dougherty.

The book comprises three parts. The first part provides the state-of-the-art of robots for endoscopy (endorobots), including devices already available in the market and those that are still at the R&D stage. The second part focusses on the engineering design; it includes the use of polymers for soft robotics, comparing their advantages and limitations with those of their more rigid counterparts. The third part includes the project management of a multidisciplinary team, the health cost of current technology, and how a cost-effective device can have a substantial impact on the market. It also includes information on data governance, ethical and legal frameworks, and all steps needed to make this new technology available.

The book provides updated knowledge on cerebrovascular imaging-related anatomy and topographic maps for neurologists, neurosurgeons, neuroradiologists, and neurovascular researchers as well as medical or neuroscience students. It includes not only high-resolution cerebrovascular images but also topographic brain maps.The topographic brain maps will provide (a) 'recently-updated' knowledge on cerebrovascular territories, which are of key clinical importance in patients with stroke; (b) age-specific WMH maps that allows a 'tailored patient-specific' interpretation in stroke- and vascular dementia-related clinical practice; and (c) easy-to-use 'reference maps' that allow prompt and reliable visual estimation of cerebral infarct volumes. This pocket book will serve as the best format for these image datasets to be looked up and referenced by the vast majority of readers.Apart from being a handy reference for neurovascular or neuroscience researchers, this book can also be used as a supplementary text book in medical schools.

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 Models for Medical Imaging explains the concepts of Deep Learning (DL) and its importance in medical imaging and/or healthcare using two different case studies: a) cytology image analysis and b) coronavirus (COVID-19) prediction, screening, and decision-making, using publicly available datasets in their respective experiments. Of many DL models, custom Convolutional Neural Network (CNN), ResNet, InceptionNet and DenseNet are used. The results follow 'with' and 'without' transfer learning (including different optimization solutions), in addition to the use of data augmentation and ensemble networks. DL models for medical imaging are suitable for a wide range of readers starting from early career research scholars, professors/scientists to industrialists.

Ultrasound Guided Musculoskeletal Procedures in Sports Medicine: A Practical Atlas provides the support practitioners need based on practical, first-hand experience of a Sports and Exercise Medicine Physician who trained in musculoskeletal sonography. Over the years, and with much practice, the lessons learned and techniques developed are summarized with relevant pictures that guide those undertaking the procedure. As musculoskeletal ultrasound forms an important tool for physicians working in this field of medicine, this book helps physicians provide increasing expectation for patients who want a safe, guided procedure when clinically warranted. While an understanding of ultrasound imaging is essential prior to ultrasound guided procedures, there are few practical guides that provide practicing clinicians with a quick reference when faced with a procedure. This book fills that void.

Over the past 15 years, there has been a growing need in the medical image computing community for principled methods to process nonlinear geometric data. Riemannian geometry has emerged as one of the most powerful mathematical and computational frameworks for analyzing such data. Riemannian Geometric Statistics in Medical Image Analysis is a complete reference on statistics on Riemannian manifolds and more general nonlinear spaces with applications in medical image analysis. It provides an introduction to the core methodology followed by a presentation of state-of-the-art methods. Beyond medical image computing, the methods described in this book may also apply to other domains such as signal processing, computer vision, geometric deep learning, and other domains where statistics on geometric features appear. As such, the presented core methodology takes its place in the field of geometric statistics, the statistical analysis of data being elements of nonlinear geometric spaces. The foundational material and the advanced techniques presented in the later parts of the book can be useful in domains outside medical imaging and present important applications of geometric statistics methodology Content includes: The foundations of Riemannian geometric methods for statistics on manifolds with emphasis on concepts rather than on proofs Applications of statistics on manifolds and shape spaces in medical image computing Diffeomorphic deformations and their applications As the methods described apply to domains such as signal processing (radar signal processing and brain computer interaction), computer vision (object and face recognition), and other domains where statistics of geometric features appear, this book is suitable for researchers and graduate students in medical imaging, engineering and computer science.

When a radiological image includes unfamiliar features, how do you decide whether it is normal variation or pathological abnormality? If you decide an abnormality is present, can you make a diagnosis from the image alone? Pearls and Pitfalls in Musculoskeletal Imaging differentiates less common findings or normal variant mimickers from the more common similar appearing diseases, helping you make a quick and accurate diagnosis. Musculoskeletal disorders of the shoulder, upper extremity, pelvis, and lower extremity are described in over 90 cases, highly illustrated with over 300 radiographic, CT, MRI and ultrasound images. Each case follows a standard format: imaging description, importance, typical clinical scenario, differential diagnosis and teaching point, enabling you to locate key information quickly. Pearls and Pitfalls in Musculoskeletal Imaging will help you spot artifacts, mimics and other unusual conditions, enabling you to avoid misdiagnosis and prevent mismanagement. An essential diagnostic tool for radiologists at every level.

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers.

Important pediatric radiology cases and board-type Q&A review to help you pass your exam! Pediatric radiology provides an opportunity to care for perhaps the most vulnerable patients of all, from prenatal life through adolescence. Pediatric Imaging, Second Edition by Richard Gunderman and Lisa Delaney features 100 new cases along with two board-type multiple-choice questions for each. A wide spectrum of cases focusing on radiology in children - from basic to advanced - are strategically designed to increase a resident's knowledge and provide robust exam preparation. For maximum ease of self-assessment, each case begins with the clinical presentation on the right-hand page; study that and then turn the page for imaging findings, differential diagnoses with the definitive diagnosis, essential facts, pearls and pitfalls, and more. Key Highlights Multiple images for every case demonstrate how a condition appears in different modalities Easy-to-read bulleted formatting and concise, point-by-point presentation of the Essential Facts enables learning and retention of high-yield facts and skill-building in radiologic diagnosis Online access to additional cases enables residents to arrange study sessions, quickly extract and master information, and prepare for theme-based radiology conferences Thieme's RadCases means cases selected to simulate what you will see on your exams, rounds, and rotations. RadCases helps you to identify the correct differential diagnosis for each case, including the most critical. The series comprehensively covers the following specialties: Breast Imaging * Cardiac Imaging * Emergency Imaging * Gastrointestinal Imaging * Genitourinary Imaging * Head and Neck Imaging * Interventional Radiology * Musculoskeletal Radiology * Neuro Imaging * Nuclear Medicine * Pediatric Imaging * Thoracic Imaging * Ultrasound Imaging Each RadCases second edition has a code allowing you one year of access to Thieme's online database of 350 cases: the 100 cases in this book plus 250 cases more. Master your cases, pass your exams, and diagnose with confidence: RadCases!

This atlas, containing a wealth of clinical and dermoscopic images, describes and illustrates the applications of dermoscopy in a wide variety of skin disorders that may be encountered in the pediatric population. Key features and other salient aspects are highlighted with the aim of enabling the clinician to reach a fast and reliable diagnosis in all cases. Dermoscopy is a non-invasive technique that allows rapid and magnified in vivo observation of the skin, with visualization of morphologic features imperceptible to the naked eye. Dermoscopy has revolutionized the approach to pigmented skin lesions, greatly improving diagnostic accuracy. Furthermore, over the past few years it has been demonstrated to be very useful in the diagnosis, follow-up, and therapeutic monitoring of a range of other skin disorders, including cutaneous/mucosal infections, ectoparasitoses, inflammatory diseases, and hair and nail abnormalities. Being non-invasive, dermoscopy is particularly suitable for use in the pediatric population, in which invasive diagnostic procedures may be problematic.