Machine Learning in Radiation Oncology: Theory and Applications (2015)
By: and and
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- Synopsis
- 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.
- Copyright:
- 2015
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9783319183053
- Related ISBNs:
- 9783319183046
- Publisher:
- Springer International Publishing
- Date of Addition:
- 09/08/19
- Copyrighted By:
- Springer International Publishing, Cham
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Science, Medicine
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
- Edited by:
- Issam El Naqa
- Edited by:
- Ruijiang Li
- Edited by:
- Martin J. Murphy
Reviews
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- by Issam El Naqa
- by Ruijiang Li
- by Martin J. Murphy
- in Nonfiction
- in Science
- in Medicine