Inspection of visible components in urine based on deep learning.

Journal: Medical physics
Published Date: May 14, 2020

Abstract

PURPOSE: Urinary particles are particularly important parameters in clinical urinalysis, especially for the diagnosis of nephropathy. Therefore, it is highly important to precisely detect urinary particles in the clinical setting. However, artificial microscopy is subjective and time consuming, and various previous detection algorithms lack the adequate accuracy. In this study, a method is proposed for the analysis of urinary particles based on deep learning.

Authors

  • Qiaoliang Li
    School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China.
  • Zhigang Yu
    Department of Biomedical Engineering, ShenZhen University, ShenZhen, 518000, China.
  • Tao Qi
    Department of Laboratory Medicine, Nangfang Hospital, Southern Medical University, GuangDong, 510515, China.
  • Lei Zheng
    Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Huanhuxi Road, Hexi District, Tianjin 300060, China.
  • Suwen Qi
    Department of In vitro Diagnostics, School of Biomedical Engineering, Shenzhen University, Shenzhen 518037, China.
  • Zhuoying He
    Department of Biomedical Engineering, ShenZhen University, ShenZhen, 518000, China.
  • Shiyu Li
    Department of Biomedical Engineering, ShenZhen University, ShenZhen, 518000, China.
  • Huimin Guan
    Department of Biomedical Engineering, ShenZhen University, ShenZhen, 518000, China.

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