An automated in vitro wound healing microscopy image analysis approach utilizing U-net-based deep learning methodology.

Journal: BMC medical imaging
Published Date: Jun 25, 2024

Abstract

BACKGROUND: The assessment of in vitro wound healing images is critical for determining the efficacy of the therapy-of-interest that may influence the wound healing process. Existing methods suffer significant limitations, such as user dependency, time-consuming nature, and lack of sensitivity, thus paving the way for automated analysis approaches.

Authors

  • Dilan Doğru
    Department of Biomedical Engineering, Graduate School of Natural and Applied Sciences, Izmir Katip Celebi University, Izmir, Turkey.
  • Gizem D Özdemir
    Department of Biomedical Engineering, Graduate School of Natural and Applied Sciences, Izmir Katip Celebi University, Izmir, Turkey.
  • Mehmet A Özdemir
    Department of Biomedical Engineering, Graduate School of Natural and Applied Sciences, Izmir Katip Celebi University, Izmir, Turkey. makif.ozdemir@ikcu.edu.tr.
  • Utku K Ercan
    Department of Biomedical Engineering, Faculty of Engineering and Architecture, Izmir Katip Celebi University, Izmir, Turkey.
  • Nermin Topaloğlu Avşar
    Department of Biomedical Engineering, Faculty of Engineering and Architecture, Izmir Katip Celebi University, Izmir, Turkey.
  • Onan Guren
    Department of Biomedical Engineering, Faculty of Enigneering and Architecture, Izmir Katip Celebi University, 35620, Cigli, Izmir, Turkey.

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