Improving generalization in MR‐to‐CT synthesis in radiotherapy by using an augmented cycle generative adversarial network with unpaired data

Purpose MR‐to‐CT synthesis is one of the first steps in the establishment of an MRI‐only workflow in radiotherapy. Current MR‐to‐CT synthesis methods in deep learning use unpaired MR and CT training images with a cycle generative adversarial network (CycleGAN) to minimize the effect of misalignment...

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Veröffentlicht in:	Medical physics (Lancaster) 2021-06, Vol.48 (6), p.3003-3010
Hauptverfasser:	Brou Boni, Kévin N. D., Klein, John, Gulyban, Akos, Reynaert, Nick, Pasquier, David
Format:	Artikel
Sprache:	eng
Schlagworte:	CycleGAN Data Analysis, Statistics and Probability Medical Physics MR‐guided radiotherapy Physics synthetic CT
Online-Zugang:	Volltext
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