Deep learning‐based motion compensation for four‐dimensional cone‐beam computed tomography (4D‐CBCT) reconstruction

Background Motion‐compensated (MoCo) reconstruction shows great promise in improving four‐dimensional cone‐beam computed tomography (4D‐CBCT) image quality. MoCo reconstruction for a 4D‐CBCT could be more accurate using motion information at the CBCT imaging time than that obtained from previous 4D‐...

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Veröffentlicht in:	Medical physics (Lancaster) 2023-02, Vol.50 (2), p.808-820
Hauptverfasser:	Zhang, Zhehao, Liu, Jiaming, Yang, Deshan, Kamilov, Ulugbek S., Hugo, Geoffrey D.
Format:	Artikel
Sprache:	eng
Schlagworte:	4D‐CBCT Algorithms Cone-Beam Computed Tomography - methods Deep Learning Four-Dimensional Computed Tomography - methods Humans Image Processing, Computer-Assisted - methods Lung Neoplasms Motion motion compensation Phantoms, Imaging Spiral Cone-Beam Computed Tomography
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