Deep learning imaging reconstruction of reduced-dose 40 keV virtual monoenergetic imaging for early detection of colorectal cancer liver metastases.

Journal: European journal of radiology
Published Date:

Abstract

OBJECTIVE: To explore whether reduced-dose (RD) gemstone spectral imaging (GSI) and deep learning image reconstruction (DLIR) of 40 keV virtual monoenergetic image (VMI) enhanced the early detection and diagnosis of colorectal cancer liver metastases (CRLM).

Authors

  • Shenglin Li
    College of Artificial Intelligence, Southwest University, Chongqing 400715, China.
  • Long Yuan
    Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, China; Second clinical school, Lanzhou University, Lanzhou, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China. Electronic address: yuanl075@163.com.
  • Ting Lu
    West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, People's Republic of China.
  • Xinmei Yang
    Department of Pharmacy, Qianfoshan Hospital Affiliated to Shandong University, Ji'nan, China.
  • Wei Ren
    Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Department of Medical Oncology, Breast Tumor Centre, Phase I Clinical Trial Centre, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
  • Luotong Wang
    CT Imaging Research Center, GE Healthcare China, No.1 Tongji South Road, Beijing, 100176, China.
  • Jun Zhao
  • Juan Deng
    Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, China; Second clinical school, Lanzhou University, Lanzhou, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China. Electronic address: 2377052591@qq.com.
  • Xianwang Liu
    Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, China; Second clinical school, Lanzhou University, Lanzhou, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China. Electronic address: 1553537867@qq.com.
  • Caiqiang Xue
    Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, China; Second clinical school, Lanzhou University, Lanzhou, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China. Electronic address: 1102599617@qq.com.
  • Qiu Sun
    Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, China; Second clinical school, Lanzhou University, Lanzhou, China. Electronic address: today-go@163.com.
  • Wenjuan Zhang
    Department of Biopharmaceutics, School of Pharmacy, Shenyang Pharmaceutical University, Wenhua Road, Shenyang 110016, China.
  • Junlin Zhou
    Department of Radiology, Lanzhou University Second Hospital, 730030 Lanzhou, Gansu, China.