Automatic Detection and Scoring of Kidney Stones on Noncontrast CT Images Using S.T.O.N.E. Nephrolithometry: Combined Deep Learning and Thresholding Methods.

Journal: Molecular imaging and biology
Published Date:

Abstract

PURPOSE: To develop and validate a deep learning and thresholding-based model for automatic kidney stone detection and scoring according to S.T.O.N.E. nephrolithometry.

Authors

  • Yingpu Cui
    Department of Radiology, Peking University First Hospital, 8, Xishiku Street, Xicheng District, Beijing, 100034, China.
  • Zhaonan Sun
    Department of Radiology, Peking University First Hospital, 8, Xishiku Street, Xicheng District, Beijing, 100034, China.
  • Shuai Ma
  • Weipeng Liu
    College of Materials and Energy, South China Agricultural University, Guangzhou, 510642, China.
  • Xiangpeng Wang
    Beijing Smart Tree Medical Technology Co. Ltd., Beijing, China.
  • Xiaodong Zhang
    The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • XiaoYing Wang