Deep learning image reconstruction for low-kiloelectron volt virtual monoenergetic images in abdominal dual-energy CT: medium strength provides higher lesion conspicuity.

Abstract

Authors

• Jingyu Zhong
  Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111 Xianxia Road, Changning District, Shanghai, 200336, China.
• Yangfan Hu
  Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200233, China.
• Yue Xing
  Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111 Xianxia Road, Shanghai, 200336, China.
• Lingyun Wang
  Department of Mechanical and Electrical Engineering, Xiamen University, Xiamen 361005, China. wangly@xmu.edu.cn.
• Jianying Li
  CT Research Center, GE Healthcare China, Beijing 100176, China.
• Wei Lu
  Department of Pharmacy, Taihe Hospital, Hubei University of Medicine, Shiyan, China.
• Xiaomeng Shi
  From the Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Rd, Shanghai 200080, China (B.J., N.L., X.X.); CT Imaging Research Center, GE Healthcare China, Shanghai, China (X.S., S.Z., J.L.); and Departments of Epidemiology (G.H.d.B.) and Radiology (R.V.), University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
• Defang Ding
  Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111 Xianxia Road, Shanghai, 200336, China.
• Xiang Ge
  Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200336, China.
• Huan Zhang
  Department of Plant Protection, Zhejiang University, 866 Yuhangtang Road, 5 Hangzhou 310058, China.
• Weiwu Yao
  Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111 Xianxia Road, Changning District, Shanghai, 200336, China. yaoweiwuhuan@163.com.

Keywords

External Resources