Swin2SR network for reconstructing chest super-resolution CT images
10.13929/j.issn.1003-3289.2025.05.009
- VernacularTitle:Swin2SR网络用于重建胸部超分辨率CT图像
- Author:
Qingyao LI
1
;
Min XU
;
Yaping ZHANG
;
Lu ZHANG
;
Lingyun WANG
;
Zhijie PAN
;
Xueqian XIE
Author Information
1. 上海市第一人民医院放射科,上海 200080;上海理工大学健康科学与工程学院,上海 200093
- Publication Type:Journal Article
- Keywords:
lung diseases;
tomography,X-ray computed;
quality control;
artificial intelligence
- From:
Chinese Journal of Medical Imaging Technology
2025;41(5):739-743
- CountryChina
- Language:Chinese
-
Abstract:
Objective To observe the value of Swin2SR network based on Transformer architecture for reconstructing chest super-resolution CT images.Methods Chest CT data of 218 patients were retrospectively collected.Swin2SR model based on Transformer architecture was adopted to enhance standard 512 matrix(512 × 512)CT images(standard-512 group)into 1 024(SR-1 024 group)and 2 048(SR-2 048 group)matrix SR CT images,respectively.Subjective and objective evaluation of image quality were performed,and the results were compared among groups.Results The subjective scores of overall imaging quality and lesion clarity in SR-1 024 and SR-2 048 groups were both higher than those in standard-512 group(all P＜0.05),while no significant difference was found between the former two(P＞0.05).Meanwhile,no significant difference of objective indexes of imaging quality was observed among 3 groups(all P＞0.05).Conclusion Swin2SR model could reconstruct chest SR CT images without increasing noise and improve imaging quality.
