Machine Learning in Radiation Oncology Theory and Applications

Machine Learning in Radiation Oncology
  • Engels
  • Hardcover
  • 9783319183046
  • Druk: 2015 ed.
  • juni 2015
  • 336 pagina's
Alle productspecificaties

Samenvatting

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.

Productspecificaties

Inhoud

Taal
Engels
Bindwijze
Hardcover
Druk
2015 ed.
Verschijningsdatum
2015-06-30
Aantal pagina's
336 pagina's
Illustraties
Met illustraties

Betrokkenen

Redacteur
Issam El Naqa
Co-redacteur
Martin J. Murphy
Uitgever
Springer International Publishing Ag

EAN

EAN
9783319183046

Overige kenmerken

Extra groot lettertype
Nee
Oorspronkelijke releasedatum
2015-06-20
Subtitel
Theory and Applications
Thema Subject Code
MJCL1

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