Abstract

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Title:: CBCT image correction for nasopharyngeal carcinoma based on cycle-consistent generative adversarial network

Author(s):: QUAN Kerun1; CHENG Pinjing1; CHEN Rongqin2; BAI Penggang2; CHEN Jihong2; HUANG Miaoyun3; CHEN Yanyu1; HONG Jiabiao2; 1. School of Nuclear Science and Technology, University of South China, Hengyang 421001, China 2. Department of Radiation Oncology, Fujian Provincial Cancer Hospital, Fuzhou 350014, China 3. Department of Radiation Oncology, Fujian Medical University Union Hospital, Fuzhou 350001, China

Keywords:: Keywords: nasopharyngeal carcinoma cone-beam computed tomography cycle-consistent generative adversarial network

Abstract:: Abstract: Objective To realize HU correction for cone-beam computed tomography (CBCT) image by translating CBCT image into synthesized CT (sCT) via cycle-consistent generative adversarial network (CycleGAN). Methods Thirty-nine patients with nasopharyngeal carcinoma who underwent radiotherapy in Fujian Provincial Cancer Hospital were enrolled in the study and received clinical CT and CBCT scans. Taking CBCT image as benchmark, rigid registration algorithm was used for registration between clinical CT and CBCT, thereby obtaining resampling planning CT (pCT). Threshold segmentation and morphological processing were used to obtain the body region of the paired image as a mask and moreover, masking and normalizing pre-processing were carried out on the paired images. CycleGAN was established and then used to generate sCT images. Mean absolute error and mean error which were calculated based on voxels were adopted for comparing the differences between sCT and pCT. Results The comparison between sCT images and pCT images of test set showed that mean absolute error and mean error were (99.00±15.37) HU and (-24.00±12.64) HU for the whole body, and (48.00±7.45) HU and (-7.00±8.96) HU for soft tissues. Conclusion CycleGAN can be used for the HU correction for CBCT image, and the generated sCT image which has similar HU value and smoothness with pCT image can be used for dose calculation in radiotherapy.