64%OFF
Machine Learning in Radiation Oncology: Theory and Applications
El Naqa
€ 130.52
€ 46.48
FREE Delivery in Ireland
Description for Machine Learning in Radiation Oncology: Theory and Applications
Hardback. .
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 ... Read more
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 ... Read more
Product Details
Publisher
Springer International Publishing AG
Format
Hardback
Publication date
2015
Condition
New
Number of Pages
336
Place of Publication
Cham, Switzerland
ISBN
9783319183046
SKU
V9783319183046
Shipping Time
Usually ships in 4 to 8 working days
Ref
99-1
Reviews for Machine Learning in Radiation Oncology: Theory and Applications