相似文献/References:
[1]陈伟国,贺捷新,莫天澜,等. 低剂量CT心肌灌注鲁棒去卷积参数成像方法[J].中国医学物理学杂志,2017,34(11):1131.[doi:DOI:10.3969/j.issn.1005-202X.2017.11.010]
CHEN Weiguo,HE Jiexin,MO Tianlan,et al. Robust deconvolution for low-dose CT myocardial perfusion imaging[J].Chinese Journal of Medical Physics,2017,34(02):1131.[doi:DOI:10.3969/j.issn.1005-202X.2017.11.010]
[2]谢丰雪,杨帆,冯维,等.基于深度学习的低剂量CT图像去噪[J].中国医学物理学杂志,2022,39(5):547.[doi:DOI:10.3969/j.issn.1005-202X.2022.05.004]
XIE Fengxue,YANG Fan,FENG Wei,et al.Low-dose CT image denoising based on deep learning[J].Chinese Journal of Medical Physics,2022,39(02):547.[doi:DOI:10.3969/j.issn.1005-202X.2022.05.004]
[3]洪启帆,玄祖兴,李雅馨.基于全卷积神经网络的低剂量CT去噪算法[J].中国医学物理学杂志,2023,40(6):695.[doi:DOI:10.3969/j.issn.1005-202X.2023.06.005]
HONG Qifan,XUAN Zuxing,LI Yaxin.Fully convolutional neural network based algorithm for low-dose CT image denoising[J].Chinese Journal of Medical Physics,2023,40(02):695.[doi:DOI:10.3969/j.issn.1005-202X.2023.06.005]
[4]李晓增,王宝珠,郭志涛,等.一种用于低剂量CT的微小细节保护CNN与Transformer融合去噪方法[J].中国医学物理学杂志,2024,41(7):842.[doi:1005-202X(2024)07-0842-09]
LI Xiaozeng,WANG Baozhu,GUO Zhitao,et al.Low-dose CT denoising method with CNN and Transformer to preserve tiny details[J].Chinese Journal of Medical Physics,2024,41(02):842.[doi:1005-202X(2024)07-0842-09]