In Vivo Time-Resolved Fluorescence Detection of Liver Cancer Supported by Machine Learning.

Journal: Lasers in surgery and medicine
Published Date: Nov 17, 2024

Abstract

OBJECTIVES: One of the widely used optical biopsy methods for monitoring cellular and tissue metabolism is time-resolved fluorescence. The use of this method in optical liver biopsy has a high potential for studying the shift in energy-type production from oxidative phosphorylation to glycolysis and changes in the antioxidant defense of malignant cells. On the other hand, machine learning methods have proven to be an excellent solution to classification problems in medical practice, including biomedical optics. We aim to combine time-resolved fluorescence measurements and machine learning to automate the division of liver parenchyma and tumors (primary malignant, metastases and benign tumors) into classes.

Authors

  • Elena V Potapova
    Research & Development Center of Biomedical Photonics, Orel State University, Orel, Russia.
  • Valery V Shupletsov
    Research & Development Center of Biomedical Photonics, Orel State University, Orel, Russia.
  • Viktor V Dremin
    Research & Development Center of Biomedical Photonics, Orel State University, Orel, Russia.
  • Evgenii A Zherebtsov
    Optoelectronics and Measurement Techniques Unit, University of Oulu, Oulu, Finland.
  • Andrian V Mamoshin
    Research & Development Center of Biomedical Photonics, Orel State University, Orel, Russia.
  • Andrey V Dunaev
    Research & Development Center of Biomedical Photonics, Orel State University, Orel, Russia.

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