Convolutional neural network advances in demosaicing for fluorescent cancer imaging with color-near-infrared sensors.

Journal: Journal of biomedical optics
PMID: 39045222

Abstract

SIGNIFICANCE: Single-chip imaging devices featuring vertically stacked photodiodes and pixelated spectral filters are advancing multi-dye imaging methods for cancer surgeries, though this innovation comes with a compromise in spatial resolution. To mitigate this drawback, we developed a deep convolutional neural network (CNN) aimed at demosaicing the color and near-infrared (NIR) channels, with its performance validated on both pre-clinical and clinical datasets.

Authors

  • Yifei Jin
    University of Illinois at Urbana-Champaign, Department of Electrical and Computer Engineering, Urbana, Illinois, United States.
  • Borislav Kondov
    Ss. Cyril and Methodius University of Skopje, Department of Thoracic and Vascular Surgery, Skopje, North Macedonia.
  • Goran Kondov
    Ss. Cyril and Methodius University of Skopje, Department of Thoracic and Vascular Surgery, Skopje, North Macedonia.
  • Sunil Singhal
    University of Pennsylvania, Perelman School of Medicine, Department of Thoracic Surgery, Philadelphia, Pennsylvania, United States.
  • Shuming Nie
    Biomedical Research Centre , Mills Breast Cancer Research Institute and Carle Foundation Hospital , Urbana , Illinois 61801 , United States.
  • Viktor Gruev
    University of Illinois at Urbana-Champaign, Department of Electrical and Computer Engineering, Urbana, Illinois, United States.

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