Utilizing convolutional neural networks for discriminating cancer and stromal cells in three-dimensional cell culture images with nuclei counterstain.

Journal: Journal of biomedical optics
PMID: 39184400

Abstract

SIGNIFICANCE: Accurate cell segmentation and classification in three-dimensional (3D) images are vital for studying live cell behavior and drug responses in 3D tissue culture. Evaluating diverse cell populations in 3D cell culture over time necessitates non-toxic staining methods, as specific fluorescent tags may not be suitable, and immunofluorescence staining can be cytotoxic for prolonged live cell cultures.

Authors

  • Huu Tuan Nguyen
    Massachusetts Institute of Technology (MIT), Department of Mechanical Engineering and Department of Biological Engineering, Cambridge, Massachusetts, United States.
  • Nicholas Pietraszek
    Massachusetts Institute of Technology (MIT), Department of Mechanical Engineering and Department of Biological Engineering, Cambridge, Massachusetts, United States.
  • Sarah E Shelton
    Massachusetts Institute of Technology (MIT), Department of Mechanical Engineering and Department of Biological Engineering, Cambridge, Massachusetts, United States.
  • Kwabena Arthur
    Massachusetts Institute of Technology (MIT), Department of Mechanical Engineering and Department of Biological Engineering, Cambridge, Massachusetts, United States.
  • Roger D Kamm
    Massachusetts Institute of Technology (MIT), Department of Mechanical Engineering and Department of Biological Engineering, Cambridge, Massachusetts, United States.

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