Artificial Intelligence in Radiation Oncology and Biomedical Physics

图书简介

This pioneering book explores how machine learning and other AI techniques impact millions of cancer patients who benefit from ionizing radiation. It features contributions from global researchers and clinicians, focusing on the clinical applications of machine learning for medical physics.AI and machine learning have attracted much recent attention and are being increasingly adopted in medicine, with many clinical components and commercial software including aspects of machine learning integration. General principles and important techniques in machine learning are introduced, followed by discussion of clinical applications, particularly in radiomics, outcome prediction, registration and segmentation, treatment planning, quality assurance, image processing, and clinical decision-making. Finally, a futuristic look at the role of AI in radiation oncology is provided. This book brings medical physicists and radiation oncologists up to date with the most novel applications of machine learning to medical physics. Practitioners will appreciate the insightful discussions and detailed descriptions in each chapter. Its emphasis on clinical applications reaches a wide audience within the medical physics profession.

Authors.....................................................................................................................ix Contributors.............................................................................................................xi 1. AI Applications in Radiation Therapy and Medical Physics.................1 Issam El Naqa 2. Machine Learning for Image-Based Radiotherapy Outcome Prediction........................................................................................................25 Bulat Ibragimov 3. Metric Predictions for Machine and Patient-Specific Quality Assurance........................................................................................................53 Alon Witztum, Gilmer Valdes, and Maria F. Chan 4. Data-Driven Treatment Planning, Plan QA, and Fast Dose Calculation......................................................................................................63 Yong Yang, Lei Xing, Nataliya Kovalchuk, Charles Huang, Yusuke Nomura, Weigang Hu, and Jiawei Fan 5. Reinforcement Learning for Radiation Therapy Planning and Image Processing........................................................................................... 87 Dan Nguyen, Chenyang Shen, Xun Jia, and Steve Jiang 6. Image Registration and Segmentation......................................................99 Tomi F. Nano, Carlos Cardenas, and Dante P. I. Capaldi 7. Motion Management and Image-Guided Radiation Therapy........... 125 Dante P.I. Capaldi, Paul J. Keall, and Tomi F. Nano 8. Outlook of AI in Medical Physics and Radiation Oncology.............. 145 Daniel X. Yang, Arman Avesta, Rachel Choi, and Sanjay Aneja Index........................

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Artificial Intelligence in Radiation Oncology and Biomedical Physics（Imaging in Medical Diagnosis and Therapy） 放射肿瘤学与生物医学物理学人工智能手册 生物医学工程学

Artificial Intelligence in Radiation Oncology and Biomedical Physics（Imaging in Medical Diagnosis and Therapy）

放射肿瘤学与生物医学物理学人工智能手册
生物医学工程学