Customized Prediction of Respiratory Motion View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2014

AUTHORS

Suk Jin Lee , Yuichi Motai

ABSTRACT

Accurate prediction of the respiratory motion would be beneficial to the treatment of thoracic and abdominal tumors. However, a wide variety of breathing patterns can make it difficult to predict the breathing motion with explicit models. We proposed a respiratory motion predictor, i.e., customized prediction with multiple patient interactions using Neural network (CNN). More... »

PAGES

91-107

Book

TITLE

Prediction and Classification of Respiratory Motion

ISBN

978-3-642-41508-1
978-3-642-41509-8

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-41509-8_5

DOI

http://dx.doi.org/10.1007/978-3-642-41509-8_5

DIMENSIONS

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