Development and validation of a deep learning-based laparoscopic system for improving video quality.

Journal: International journal of computer assisted radiology and surgery
PMID: 36243805

Abstract

PURPOSE: A clear surgical field of view is a prerequisite for successful laparoscopic surgery. Surgical smoke, image blur, and lens fogging can affect the clarity of laparoscopic imaging. We aimed to develop a real-time assistance system (namely LVQIS) for removing these interfering factors during laparoscopic surgery, thereby improving laparoscopic video quality.

Authors

  • Qingyuan Zheng
    Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
  • Rui Yang
    Department of Biomedical Informatics, Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore.
  • Xinmiao Ni
    Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
  • Song Yang
    Key Laboratory of Pesticide Toxicology&Application Technique, College of Plant Protection, Shandong Agricultural University, Tai'an 271018, China.
  • Zhengyu Jiang
    Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
  • Lei Wang
    Department of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Zhiyuan Chen
    Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
  • Xiuheng Liu
    Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.

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