Feasibility of predicting tumor motion using online data acquired during treatment and a generalized neural network optimized with offline patient tumor trajectories

Purpose The accurate prediction of intrafraction lung tumor motion is required to compensate for system latency in image‐guided adaptive radiotherapy systems. The goal of this study was to identify an optimal prediction model that has a short learning period so that prediction and adaptation can com...

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Veröffentlicht in:	Medical physics (Lancaster) 2018-02, Vol.45 (2), p.830-845
Hauptverfasser:	Teo, Troy P., Ahmed, Syed Bilal, Kawalec, Philip, Alayoubi, Nadia, Bruce, Neil, Lyn, Ethan, Pistorius, Stephen
Format:	Artikel
Sprache:	eng
Schlagworte:	DMLC tracking image‐guided adaptive radiotherapy sliding window neural network system latency tumor motion prediction
Online-Zugang:	Volltext
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