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Machine Learning in Radiation Oncology

Theory and Applications

Editors: El Naqa, Issam, Li, Ruijiang, Murphy, Martin J. (Eds.)

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  • ​Provides a complete overview of the role of machine learning in radiation oncology and medical physics
  • Covers the use of machine learning in quality assurance, computer-aided detection, image-guided radiotherapy, respiratory motion management, and outcome prediction
  • Presents important relevant background information
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eBook $99.00
price for USA in USD (gross)
  • ISBN 978-3-319-18305-3
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $139.99
price for USA in USD
  • ISBN 978-3-319-18304-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $129.00
price for USA in USD
  • Customers within the U.S. and Canada please contact Customer Service at +1-800-777-4643, Latin America please contact us at +1-212-460-1500 (24 hours a day, 7 days a week). Pre-ordered printed titles are excluded from promotions.
  • Due: November 18, 2016
  • ISBN 978-3-319-35464-4
  • Free shipping for individuals worldwide
About this book

​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.

Table of contents (18 chapters)

Table of contents (18 chapters)

Buy this book

eBook $99.00
price for USA in USD (gross)
  • ISBN 978-3-319-18305-3
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $139.99
price for USA in USD
  • ISBN 978-3-319-18304-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $129.00
price for USA in USD
  • Customers within the U.S. and Canada please contact Customer Service at +1-800-777-4643, Latin America please contact us at +1-212-460-1500 (24 hours a day, 7 days a week). Pre-ordered printed titles are excluded from promotions.
  • Due: November 18, 2016
  • ISBN 978-3-319-35464-4
  • Free shipping for individuals worldwide
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Bibliographic Information

Bibliographic Information
Book Title
Machine Learning in Radiation Oncology
Book Subtitle
Theory and Applications
Editors
  • Issam El Naqa
  • Ruijiang Li
  • Martin J. Murphy
Copyright
2015
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-18305-3
DOI
10.1007/978-3-319-18305-3
Hardcover ISBN
978-3-319-18304-6
Softcover ISBN
978-3-319-35464-4
Edition Number
1
Number of Pages
XIV, 336
Number of Illustrations
60 b/w illustrations, 67 illustrations in colour
Topics