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. | Medical Image Synthesis Methods and Clinical Applications