This book includes detailed explanations of the underlying technologies and concepts used in Artificial Intelligence (AI) and Machine Learning (ML) in the context of nuclear medicine and hybrid imaging. A diverse team of authors, including pioneers in the field and respected experts from leading international institutions, share their insights, opinions and outlooks on this exciting topic. A wide range of clinical applications are discussed, from brain applications to body indications, as well as the applicability of AI and ML for cardio-vascular conditions. The book also considers the potential impact of theranostics. To balance the technology-heavy and disease-specific applications, it also discusses ethical / legal issues, economic realities and the human factor, the physician. Though this discussion is not based on research and outcomes, it provides important insights into the ramifications of how AI and ML could transform Nuclear Medicine and Hybrid Imaging practice. As the first work highlighting the role of these concepts specifically in this field, rather than for medical imaging in general, this book offers a valuable resource for Nuclear Medicine Physicians, Radiologists, Physicists, Medical Imaging Administrators and Nuclear Medicine Technologists alike.

This book includes detailed explanations of the underlying technologies and concepts used in Artificial Intelligence (AI) and Machine Learning (ML) in the context of nuclear medicine and hybrid imaging. A diverse team of authors, including pioneers in the field and respected experts from leading international institutions, share their insights, opinions and outlooks on this exciting topic. A wide range of clinical applications are discussed, from brain applications to body indications, as well as the applicability of AI and ML for cardio-vascular conditions. The book also considers the potential impact of theranostics. To balance the technology-heavy and disease-specific applications, it also discusses ethical / legal issues, economic realities and the human factor, the physician. Though this discussion is not based on research and outcomes, it provides important insights into the ramifications of how AI and ML could transform Nuclear Medicine and Hybrid Imaging practice. As the first work highlighting the role of these concepts specifically in this field, rather than for medical imaging in general, this book offers a valuable resource for Nuclear Medicine Physicians, Radiologists, Physicists, Medical Imaging Administrators and Nuclear Medicine Technologists alike.

This book provides an overview of current and potential applications of artificial intelligence (AI) for cardiothoracic imaging. Most AI systems used in medical imaging are data-driven and based on supervised machine learning. Clinicians and AI specialists can contribute to the development of an AI system in different ways, focusing on their respective strengths. Unfortunately, communication between these two sides is far from fluent and, from time to time, they speak completely different languages. Mutual understanding and collaboration are imperative because the medical system is based on physicians’ ability to take well-informed decisions and convey their reasoning to colleagues and patients. This book offers unique insights and informative chapters on the use of AI for cardiothoracic imaging from both the technical and clinical perspective. It is also a single comprehensive source that provides a complete overview of the entire process of the development and use of AI in clinical practice for cardiothoracic imaging. The book contains chapters focused on cardiac and thoracic applications as well more general topics on the potentials and pitfalls of AI in medical imaging. Separate chapters will discuss the valorization, regulations surrounding AI, cost-effectiveness, and future perspective for different countries and continents. This book is an ideal guide for clinicians (radiologists, cardiologists etc.) interested in working with AI, whether in a research setting developing new AI applications or in a clinical setting using AI algorithms in clinical practice. The book also provides clinical insights and overviews for AI specialists who want to develop clinically relevant AI applications.

In this issue of PET Clinics, guest editors Arman Rahmim, Babak Saboury, and Eliot Siegel bring their considerable expertise to the topic of Artificial Intelligence and PET Imaging. Provides in-depth, clinical reviews on the latest updates in AI and PET Imaging, providing actionable insights for clinical practice. Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field; Authors synthesize and distill the latest research and practice guidelines to create these timely topic-based reviews.

Neuroimaging in Parkinson's Disease and Related Disorders discusses the advances of molecular, structural and functional neuroimaging techniques associated with the etiology, pathophysiology, effects and complications of novel therapies in Parkinson's and related disorders. With new neuroimaging methodologies emerging over the past five years, this book provides a comprehensive overview of new technologies and research. Sections discuss the biomarker value of neuroimaging of the brain to understand disease progression in vivo in actual patients with Parkinson's disease and related disorders. Readers will be updated on in vivo pathology and pathophysiology in Parkinson's disease and in a number of related disorders. Also discussed is the association between clinical symptoms, clinical progression, and molecular, structural, and functional changes in the brain of patients with Parkinson's disease and related disorders. - Comprehensive overview of biomarker value of neuroimaging of the brain to understand disease progression in vivo in actual patients with Parkinson's disease and related disorders - Helps readers understand the in vivo pathology and pathophysiology in Parkinson's disease and in a number of related disorders - Discusses the association between clinical symptoms, clinical progression, and molecular, structural, and functional changes in the brain of patients with Parkinson's and related disorders

This book provides comprehensive and detailed information on the scientific bases of nuclear medicine, addressing a wide variety of topics and explaining the concepts that underlie many of the investigations and procedures performed in the field. The book is divided into six sections that cover the physics and chemistry of nuclear medicine besides associated quality assurance/quality control procedures; dosimetry and radiation biology; SPECT and PET imaging instrumentation plus CT imaging technology in hybrid modalities; data analysis including image processing, reconstruction, radiomics, image degrading correction techniques, along with image quantitation and kinetic modeling. Within these sections, particular attention is paid to recent developments and the advances in knowledge that have taken place since release of the first edition in 2011. Several entirely new chapters have been included and the remaining chapters, thoroughly updated. Innovations in the ever-expanding field of nuclear medicine are predominantly due to integration of the basic sciences with complex technological advances. This excellently illustrated book on the subject will be of interest to not only nuclear medicine physicists and physicians but also clinical scientists, radiologists, radiopharmacists, medical students and technologists.

Artificial Intelligence and Image Processing in Medical Imaging deals with the applications of processing medical images with a view of improving the quality of the data in order to facilitate better decision- making. The book covers the basics of medical imaging and the fundamentals of image processing. It explains spatial and frequency domain applications of image processing, introduces image compression techniques and their applications, and covers image segmentation techniques and their applications. The book includes object detection and classification applications and provides an overall background to statistical analysis in biomedical systems. The role of Machine Learning, including Neural Networks, Deep Learning, and the implications of the expansion of artificial intelligence is also covered. With contributions from prominent researchers worldwide, this book provides up-to-date and comprehensive coverage of AI applications in image processing where readers will find the latest information with clear examples and illustrations. - Provides the latest comprehensive coverage of the developments of AI techniques and the principles of medical imaging - Covers all aspects of medical imaging, from acquisition, the use of hardware and software, image analysis and implementation of AI in problem solving - Provides examples of medical imaging and how they're processed, including segmentation, classification, and detection

Radiology-Nuclear Medicine Diagnostic Imaging “p>Radiology-Nuclear Medicine Diagnostic Imaging: A Correlative Approach provides in-depth guidance on applying the principles of radiologic-nuclear medicine correlation to the interpretation of imaging for diagnostic, prognostic, and predictive indications. Describing the clinical implications of all major imaging modalities, this comprehensive professional reference offers one-stop coverage of the common diagnostic applications encountered by nuclear medicine physicians and radiologists in day-to-day practice. The book develops the nuclear diagnostic skills necessary to interpret combined imaging modalities and correlate radiologic findings using a disease and organ-based approach to radiologic interpretation. Thematically organized sections explore a variety of pathologies including diseases of the head and neck, gastrointestinal tract, and pulmonary, endocrine, and central nervous system. Written by internationally recognized experts, this important resource: Helps physicians better understand the clinical and treatment implications of diseases with characteristic radiologic appearances Includes detailed descriptions of nuclear medicine presentations of diseases of most organ systems combined with radiologic correlation Explains refinement of differential diagnoses in various organ systems based on specific imaging features Demonstrates how to correlate scintigraphy and PET images with radiography, CT, MRI, and other imaging techniques Includes a timely review of the application of nuclear medicine-radiology correlative imaging in research Features practical, hands-on clinical imaging references, and more than 600 color illustrations and high-resolution images throughout Radiology-Nuclear Medicine Diagnostic Imaging: A Correlative Approach is a must-have for both trainee and experienced radiologists, nuclear medicine physicians, and specialist nurses.

Image synthesis across and within medical imaging modalities is an active area of research with broad applications in radiology and radiation oncology. This book covers the principles and methods of medical image synthesis, along with state-of-the-art research. First, various traditional non-learning-based, traditional machine-learning-based, and recent deep-learning-based medical image synthesis methods are reviewed. Second, specific applications of different inter- and intra-modality image synthesis tasks and of synthetic image-aided segmentation and registration are introduced and summarized, listing and highlighting the proposed methods, study designs, and reported performances with the related clinical applications of representative studies. Third, the clinical usages of medical image synthesis, such as treatment planning and image-guided adaptive radiotherapy, are discussed. Last, the limitations and current challenges of various medical synthesis applications are explored, along with future trends and potential solutions to solve these difficulties. The benefits of medical image synthesis have sparked growing interest in a number of advanced clinical applications, such as magnetic resonance imaging (MRI)-only radiation therapy treatment planning and positron emission tomography (PET)/MRI scanning. This book will be a comprehensive and exciting resource for undergraduates, graduates, researchers, and practitioners.