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Paired cycle‐GAN‐based image correction for quantitative cone‐beam computed tomography
253
Zitationen
9
Autoren
2019
Jahr
Abstract
The authors have developed a novel deep learning-based method to generate high-quality corrected CBCT images. The proposed method increases onboard CBCT image quality, making it comparable to that of the planning CT. With further evaluation and clinical implementation, this method could lead to quantitative adaptive radiation therapy.
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