Xiaofeng Yang is the Paul W. Doetsch Professor and Vice Chair for Medical Physics Research in the Department of Radiation Oncology at Emory University School of Medicine. He directs the Deep Biomedical Imaging Lab, where he develops innovative AI-enabled analytical and computational methods to advance quantitative imaging in cancer diagnosis and treatment, with the goal of improving the accuracy and precision of cancer radiotherapy. Dr. Yang also holds adjunct faculty appointments in the Medical Physics and Machine Learning programs at the Georgia Institute of Technology, the Department of Biomedical Informatics at Emory University, and the Wallace H. Coulter Department of Biomedical Engineering at Emory University and Georgia Tech. He is a Fellow of SPIE.Tonghe Wang, PhD, DABR, is an assistant attending physicist in the Department of Medical Physics at the Memorial Sloan Kettering at main campus. Dr. Wang received his BS in physics from Peking University in China in 2013 and PhD in medical physics from Georgia Institute of Technology in 2017, with research experience in iterative CT reconstruction. Dr. Wang completed a medical physics residency at Emory University in 2019 and stayed at Emory as an assistant professor and board-certified medical physicist before joining Memorial Sloan Kettering Cancer Center in 2022. Dr. Wang provide clinical physics services in all aspects of radiation therapy and specialize in brachytherapy and Gamma Knife. Dr. Wang is currently working on a variety of research projects, including image segmentation and image synthesizing. He is interested in improving automation in clinical workflow and enabling advanced treatment strategy.

• Introduction. Chapter 1 Medical Image Synthesis. Chapter 2 Medical Image Segmentation. Chapter 3 Medical Image Registration. Chapter 4 Empowering Innovation in Medical Imaging with AI-Based Radiomics. Chapter 5 Vision-Language Models for Medical Image Analysis. Chapter 6 AI-driven Image-Guided Radiation Therapy. Chapter 7 Adaptive Radiation Therapy. Chapter 8 Motion Management in Radiation Therapy. Chapter 9 Proton and Flash Therapy. Chapter 10 Artificial Intelligence in Brachytherapy. Chapter 11 Treatment Response Assessment and Prediction. Chapter 12 The Promise and Peril of AI in Clinical Practice. Perspectives. Bibliography. Index.