Research on the improvement of CBCT image quality based on region-discriminative generative adversarial networks in radiotherapy for cervical cancer
10.3969/j.issn.1672-8270.2024.02.001
- VernacularTitle:基于区域判别生成对抗网络的宫颈癌放射治疗锥形束CT影像质量提升研究
- Author:
Xiaoshuo HAO
1
,
2
;
Dong HUANG
;
Yao ZHENG
;
Yuefei FENG
;
Yutao HE
;
Hua YANG
;
Yang LIU
Author Information
1. 空军军医大学军事生物医学工程学系军事信息技术教研室 西安 710032
2. 生物电磁检测与智能感知陕西省重点实验室 西安 710032
- Keywords:
Generative adversarial network(GAN);
Image enhancement;
Cervical cancer;
Cone beam computed tomography(CBCT);
Radiotherapy
- From:
China Medical Equipment
2024;21(2):1-6
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To propose a model that could improve image quality of cone-beam computed tomography(CBCT),which based on region-discriminative generative adversarial networks(GAN),in radiotherapy for cervical cancer,so as to meet the requirements of self-adaptive radiotherapy for image quality.Methods:We employed a region-discriminative strategy and a generative adversarial networks idea to construct a model of improving CBCT image quality that could focus on local details of the images of radiotherapy for cervical cancer,which discriminator could improve the quality of generating local details of images.This model of image quality was applied to CBCT images of radiotherapy for cervical cancer.And then,the effects of processing image were evaluated through quantitative indicators and visualization.Results:Both texture clarity and contrast were significantly enhanced after CBCT image quality was improved.The signal to noise ratio of peak value of images was increased by 47.2%,and the indicator of similarity of structure was enhanced to>0.838.Compared with other model,both visualization and indicators can appear better efficiency of model.Compared with Unet network and CycleGAN network,the similarities of structure were respectively increased by 11.88% and 19.54%,and the signal to noise ratios were respectively increased by 19.75% and 25.99%.Conclusion:The GAN bases on region-discrimination can significantly improve the quality of generating integral and detailed CBCT image of radiotherapy for cervical cancer,which can provide new technical pathway for image quality of CBCT with low dose,and can play an important role for improving safety and effectiveness of radiotherapy.It has importantly clinical value for formulating and executing radiotherapy plan.
