Artificial Intelligence in Radiation Oncology and Biomedical Physics

This book explores the impact of machine learning and other AI techniques on cancer patients who benefit from ionizing radiation, focusing on clinical applications in medical physics. It introduces key principles and techniques, discusses radiomics, outcome prediction, registration, segmentation, treatment planning, quality assurance, image processing, and clinical decision-making, and provides a futuristic look at AI's role in radiation oncology.

Format: Hardback
Length: 172 pages
Publication date: 14 August 2023
Publisher: Taylor & Francis Ltd

This groundbreaking work delves into the profound impact of machine learning and other advanced AI techniques on the lives of millions of cancer patients who rely on ionizing radiation for treatment. Drawing upon the expertise of global researchers and clinicians, the book focuses specifically on the clinical applications of machine learning in the realm of medical physics.

AI and machine learning have emerged as hot topics in the medical field, with numerous clinical components and commercial software incorporating machine learning integration. In this book, we embark on a comprehensive journey to explore the fundamental principles and essential techniques of machine learning. We then delve into the realm of clinical applications, particularly in radiomics, outcome prediction, registration and segmentation, treatment planning, quality assurance, image processing, and clinical decision-making.

To conclude, this book offers a visionary perspective on the future role of AI in radiation oncology. It serves as a valuable resource for medical physicists and radiation oncologists, providing them with the latest advancements and innovative applications of machine learning to medical physics. By leveraging the power of AI, we can enhance the precision, efficiency, and effectiveness of cancer treatment, ultimately improving patient outcomes and quality of life.

Dimension: 234 x 156 (mm)
ISBN-13: 9780367538101