| Description |
1 online resource (xiv, 336 pages) : illustrations (some color) |
| Bibliography |
Includes bibliographical references and index. |
| Note |
Online resource; title from PDF title page (SpringerLink, viewed June 23, 2015). |
| Summary |
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. |
| Subject |
Artificial intelligence -- Medical applications.
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Machine learning.
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Radiotherapy -- Data processing.
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HEALTH & FITNESS / Holism.
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HEALTH & FITNESS / Reference.
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MEDICAL / Alternative Medicine.
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MEDICAL / Atlases.
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MEDICAL / Essays.
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MEDICAL / Family & General Practice.
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MEDICAL / Holistic Medicine.
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MEDICAL / Osteopathy.
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Artificial intelligence -- Medical applications.
(OCoLC)fst00817267
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Machine learning. (OCoLC)fst01004795
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Radiotherapy -- Data processing.
(OCoLC)fst01088353
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| Added Author |
El Naqa, Issam, editor.
|
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Li, Ruijiang, editor.
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Murphy, Martin J., Ph. D., editor.
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| Other Form: |
Printed edition: 9783319183046 |
| Standard No. |
10.1007/978-3-319-18305-3 doi |
| ISBN |
9783319183053 (electronic bk.) |
|
3319183052 (electronic bk.) |
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