A deep learning algorithm to improve readers' interpretation and speed of pancreatic cystic lesions on dual-phase enhanced CT.

Journal: Abdominal radiology (New York)
Published Date: Mar 27, 2022

Abstract

PURPOSE: To develop a deep learning model (DLM) to improve readers' interpretation and speed in the differentiation of pancreatic cystic lesions (PCLs) on dual-phase enhanced CT, and a low contrast media dose, external testing set validated the model.

Authors

  • Xiheng Wang
    Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, People's Republic of China.
  • Zhaoyong Sun
    Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, People's Republic of China.
  • Huadan Xue
    From the Department of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China. Electronic address: bjdanna95@163.com.
  • Taiping Qu
    Deepwise AI Lab, Deepwise Inc., Beijing, China.
  • Sihang Cheng
    Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, People's Republic of China.
  • Juan Li
    Department of Hygienic Inspection, School of Public Health, Jilin University 1163 Xinmin Street Changchun 130021 Jilin China songxiuling@jlu.edu.cn li_juan@jlu.edu.cn jinmh@jlu.edu.cn +86 43185619441.
  • Yatong Li
    Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, People's Republic of China.
  • Li Mao
    Deepwise AI Lab, Deepwise Inc, No.8 Haidian avenue, Sinosteel International Plaza, Beijing, 100080, China.
  • Xiuli Li
    Department of Obstetrics and Gynecology, General Hospital of Chinese People's Liberation Army, Beijing 100853, China.
  • Liang Zhu
    SINOPEC Research Institute of Safety Engineering Co., Ltd., Qingdao 266104, China.
  • Xiao Li
    Department of Inner Mongolia Clinical Medicine College, Inner Mongolia Medical University, Hohhot, Inner Mongolia, China.
  • Longjing Zhang
    Department of Diagnostic Radiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210002, People's Republic of China.
  • Zhengyu Jin
    Departments of Radiology, Peking Union Medical College Hospital, Beijing.
  • Yizhou Yu
    Department of Computer Science, The University of Hong Kong, Pok Fu Lam, Hong Kong.

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