医疗卫生装备2025，Vol.46Issue(5)：9-13,5.DOI:10.19745/j.1003-8868.2025080
基于改进Corediff模型的低剂量CT图像去噪方法研究
Research on low-dose CT image denoising method based on improved Corediff model
宋丽梅 1吴航 1黄艺峰 2王强 3刘冠军 1陈锋 1余明 1沈建坤2
作者信息
- 1. 军事科学院系统工程研究院,天津 300161
- 2. 联勤保障部队第910医院,福建泉州 362000
- 3. 天津科技大学电子信息与自动化学院,天津 300457
- 折叠
摘要
Abstract
Objective To propose a low-dose CT image denoising method based on an improved Corediff model to recover the detailed features of the image and enhance the image quality.Methods An RS-Corediff model was established by modifying the key component U-Net network of the Corediff model.Firstly,the residual module was introduced in the network input stage for feature extraction;secondly,a new downsampling module was designed in the U-Net network encoder,which learned the semantic information of the feature map by convolution and maintained the learning state during the downsampling process so as to fully extract the image features;thirdly,the feature splicing processing was used to further enhance the learning effect during the upsampling process of the U-Net network decoder;finally,the convolutional kernel size was modified to adjust the sensory field during the convolutional process of the whole U-Net network structure so as to obtain rich features.The RS-Corediff model was compared with the residual encoder-decoder convolutional neural network(RED-CNN)model and the Corediff model on the public dataset AAPM 2016 in order to verify its effectiveness for low-dose CT image denoising.Results The RS-Corediff model gained advantages over the RED-CNN and Corediff models with a peak signal-to-noise ratio(PSNR)of 41.269 8,structural similarity(SSIM)of 0.953 4 and root mean square error(RMSE)of 17.568 7.Conclusion The proposed method effectively preserves the texture and details of low-dose CT images during the denoising process to improve the overall quality of the images.[Chinese Medical Equipment Journal,2025,46(5):9-13]关键词
低剂量CT/图像去噪/扩散模型/Corediff模型/U-Net网络Key words
low-dose CT/image denoising/diffusion model/Corediff model/U-Net network分类
基础医学引用本文复制引用
宋丽梅,吴航,黄艺峰,王强,刘冠军,陈锋,余明,沈建坤..基于改进Corediff模型的低剂量CT图像去噪方法研究[J].医疗卫生装备,2025,46(5):9-13,5.
