Blood clot and fibrin recognition method for serum images based on deep learning.

Journal: Clinica chimica acta; international journal of clinical chemistry
PMID: 38128814

Abstract

BACKGROUND: Detecting and identifying of clots and fibrins in serum is an important process in the analysis stage before laboratory analysis. Currently, visual examination is commonly employed in clinical laboratories for this purpose. However, this method is not only time-consuming but also highly subjective and may result in misjudgments.

Authors

  • Jianping Hou
    Autobio Labtec Instruments Co.,Ltd, Zhengzhou Henan 450016, China. Electronic address: houjianping_mater@163.com.
  • Weihong Ren
    The First Affiliated Hospital of Henan University of CM, Zhengzhou Henan 450000, China.
  • Wanli Zhao
    Autobio Labtec Instruments Co.,Ltd, Zhengzhou Henan 450016, China.
  • Hang Li
    Beijing Academy of Quantum Information Sciences, Beijing 100193, China.
  • Mengnan Liu
    Autobio Labtec Instruments Co.,Ltd, Zhengzhou Henan 450016, China.
  • Hailuan Wang
    Autobio Labtec Instruments Co.,Ltd, Zhengzhou Henan 450016, China.
  • Yirui Duan
    Autobio Labtec Instruments Co.,Ltd, Zhengzhou Henan 450016, China.
  • Chao Wang
    College of Agriculture, Shanxi Agricultural University, Taigu, Shanxi, China.
  • Cong Liu
    Department of Bioengineering, University of Illinois at Chicago, 851 S Morgan St, Chicago, IL, 60607, USA.

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