Produktbild: Machine Learning in Radiation Oncology

Machine Learning in Radiation Oncology

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90,94 €

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Theory and Applications

ISBN: 3319354647
ISBN 13: 9783319354644
Herausgeber: Issam El Naqa/Ruijiang Li/Martin J Murphy
Verlag: Springer Verlag GmbH
Umfang: xiv, 336 S., 60 s/w Illustr., 67 farbige Illustr., 336 p. 127 illus., 67 illus. in color.
Erscheinungsdatum: 12.10.2016
Auflage: 1/2016
Produktform: Kartoniert
Einband: Kartoniert

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.

Artikelnummer: 9930596 Kategorie:

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Springer Verlag GmbH
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69121 Heidelberg
DE

E-Mail: juergen.hartmann@springer.com

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