Achieving high accuracy in meniscus tear detection using advanced deep learning models with a relatively small data set.

Journal: Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Published Date: Jul 17, 2024

Abstract

PURPOSE: This study aims to evaluate the effectiveness of advanced deep learning models, specifically YOLOv8 and EfficientNetV2, in detecting meniscal tears on magnetic resonance imaging (MRI) using a relatively small data set.

Authors

  • Erdal Güngör
    Department of Orthopaedics and Traumatology, Medipol University Esenler Hospital, Istanbul, Turkey.
  • Husam Vehbi
    Department of Radiology, Medipol University Esenler Hospital, Istanbul, Turkey.
  • Ahmetcan Cansın
    International School of Medicine, İstanbul Medipol University, Istanbul, Turkey.
  • Mehmet Batu Ertan
    Department of Orthopaedics and Traumatology, Medicana International Ankara Hospital, Ankara, Turkey.

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