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- No other book on this topic available
- Specifically focused on nuclear medicine and hybrid imaging
- Addresses multiple aspects of clinical nuclear medicine and hybrid imaging, not just the technological ones
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. Table of Contents- Role and Influence of Artificial Intelligence in Healthcare, Hybrid Imaging, and Molecular Imaging
- Introduction to Machine Learning: Definitions and Hybrid Imaging Applications
- Radiomics in Nuclear Medicine, Robustness, Reproducibility, and Standardization
- Evolution of AI in Medical Imaging
- The Basic Principles of Machine Learning
- Imaging Biomarkers and Their Meaning for Molecular Imaging
- Integration of Artificial Intelligence, Machine Learning, and Deep Learning into Clinically Routine Molecular Imaging
- Imaging Biobanks for Molecular Imaging: How to Integrate ML/AI into Our Databases
- Artificial Intelligence/Machine Learning in Nuclear Medicine
- AI/ML Imaging Applications in Body Oncology
- Artificial Intelligence/Machine Learning in Nuclear Medicine and Hybrid Imaging
- Artificial Intelligence Will Improve Molecular Imaging, Therapy and Theranostics. Which Are the Biggest Advantages for Therapy?
- Integrative Computational Biology, AI, and Radiomics: Building Explainable Models by Integration of Imaging, Omics, and Clinical Data
- Legal and Ethical Aspects of Machine Learning: Who Owns the Data?
- Artificial Intelligence and the Nuclear Medicine Physician: Clever Is as Clever Does
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