2023
DOI: 10.1088/1361-6560/ace754
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A hybrid method of correcting CBCT for proton range estimation with deep learning and deformable image registration

Abstract: Objective: This study aimed to develop a novel method for generating synthetic CT (sCT) from cone-beam CT (CBCT) of the abdomen/pelvis with bowel gas pockets to facilitate estimation of proton ranges. 

Approach: CBCT, the same-day repeat CT, and the planning CT (pCT) of 81 pediatric patients were used for training (n=60), validation (n=6), and testing (n=15) of the method. The proposed method hybridizes unsupervised deep learning (CycleGAN) and deformable image registration (DIR) of the pCT to… Show more

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