Machine Learning in Radiation Oncology

Theory and Applications

Martin J Murphy editor Issam El Naqa editor Ruijiang Li editor

Format:Hardback

Publisher:Springer International Publishing AG

Published:30th Jun '15

Should be back in stock very soon

Machine Learning in Radiation Oncology cover

​This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.

ISBN: 9783319183046

Dimensions: unknown

Weight: 7143g

336 pages

2015 ed.