1
|
Xie K, Gao L, Zhang H, Zhang S, Xi Q, Zhang F, Sun J, Lin T, Sui J, Ni X. Inpainting truncated areas of CT images based on generative adversarial networks with gated convolution for radiotherapy. Med Biol Eng Comput 2023:10.1007/s11517-023-02809-y. [PMID: 36897469 DOI: 10.1007/s11517-023-02809-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 02/20/2023] [Indexed: 03/11/2023]
Abstract
This study aimed to inpaint the truncated areas of CT images by using generative adversarial networks with gated convolution (GatedConv) and apply these images to dose calculations in radiotherapy. CT images were collected from 100 patients with esophageal cancer under thermoplastic membrane placement, and 85 cases were used for training based on randomly generated circle masks. In the prediction stage, 15 cases of data were used to evaluate the accuracy of the inpainted CT in anatomy and dosimetry based on the mask with a truncated volume covering 40% of the arm volume, and they were compared with the inpainted CT synthesized by U-Net, pix2pix, and PConv with partial convolution. The results showed that GatedConv could directly and effectively inpaint incomplete CT images in the image domain. For the results of U-Net, pix2pix, PConv, and GatedConv, the mean absolute errors for the truncated tissue were 195.54, 196.20, 190.40, and 158.45 HU, respectively. The mean dose of the planning target volume, heart, and lung in the truncated CT was statistically different (p < 0.05) from those of the ground truth CT ([Formula: see text]). The differences in dose distribution between the inpainted CT obtained by the four models and [Formula: see text] were minimal. The inpainting effect of clinical truncated CT images based on GatedConv showed better stability compared with the other models. GatedConv can effectively inpaint the truncated areas with high image quality, and it is closer to [Formula: see text] in terms of image visualization and dosimetry than other inpainting models.
Collapse
Affiliation(s)
- Kai Xie
- Radiotherapy Department, Second People's Hospital of Changzhou, Nanjing Medical University, Changzhou, 213000, China
- Jiangsu Province Engineering Research Center of Medical Physics, Changzhou, 213000, China
| | - Liugang Gao
- Radiotherapy Department, Second People's Hospital of Changzhou, Nanjing Medical University, Changzhou, 213000, China
- Jiangsu Province Engineering Research Center of Medical Physics, Changzhou, 213000, China
| | - Heng Zhang
- Center for Medical Physics, Nanjing Medical University, Changzhou, 213003, China
- Key Laboratory of Medical Physics, Changzhou, 213000, China
| | - Sai Zhang
- Center for Medical Physics, Nanjing Medical University, Changzhou, 213003, China
- Key Laboratory of Medical Physics, Changzhou, 213000, China
| | - Qianyi Xi
- Center for Medical Physics, Nanjing Medical University, Changzhou, 213003, China
- Key Laboratory of Medical Physics, Changzhou, 213000, China
| | - Fan Zhang
- Center for Medical Physics, Nanjing Medical University, Changzhou, 213003, China
- Key Laboratory of Medical Physics, Changzhou, 213000, China
| | - Jiawei Sun
- Radiotherapy Department, Second People's Hospital of Changzhou, Nanjing Medical University, Changzhou, 213000, China
- Jiangsu Province Engineering Research Center of Medical Physics, Changzhou, 213000, China
| | - Tao Lin
- Radiotherapy Department, Second People's Hospital of Changzhou, Nanjing Medical University, Changzhou, 213000, China
- Jiangsu Province Engineering Research Center of Medical Physics, Changzhou, 213000, China
| | - Jianfeng Sui
- Radiotherapy Department, Second People's Hospital of Changzhou, Nanjing Medical University, Changzhou, 213000, China
- Jiangsu Province Engineering Research Center of Medical Physics, Changzhou, 213000, China
| | - Xinye Ni
- Radiotherapy Department, Second People's Hospital of Changzhou, Nanjing Medical University, Changzhou, 213000, China.
- Jiangsu Province Engineering Research Center of Medical Physics, Changzhou, 213000, China.
- Center for Medical Physics, Nanjing Medical University, Changzhou, 213003, China.
- Key Laboratory of Medical Physics, Changzhou, 213000, China.
| |
Collapse
|