OA-MEN: a fusion deep learning approach for enhanced accuracy in knee osteoarthritis detection and classification using X-Ray imaging.

Journal: Frontiers in bioengineering and biotechnology
Published Date: Jan 3, 2025

Abstract

BACKGROUND: Knee osteoarthritis (KOA) constitutes the prevailing manifestation of arthritis. Radiographs function as a common modality for primary screening; however, traditional X-ray evaluation of osteoarthritis confronts challenges such as reduced sensitivity, subjective interpretation, and heightened misdiagnosis rates. The objective of this investigation is to enhance the validation and optimization of accuracy and efficiency in KOA assessment by utilizing fusion deep learning techniques.

Authors

  • Xiaolu Ren
    Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan, China.
  • Lingxuan Hou
    College of Biomedical Engineering, Sichuan University, Chengdu, Sichuan, China.
  • Shan Liu
    Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan, China.
  • Peng Wu
    Department of Orthopedics, General Hospital of Ningxia Medical University, Yinchuan, China.
  • Siming Liang
    Department of Orthopedics, General Hospital of Ningxia Medical University, Yinchuan, China.
  • Haitian Fu
    School of Clinical Medicine, Tsinghua University, Beijing, China.
  • Chengquan Li
    School of Clinical Medicine, Tsinghua University, Beijing, China.
  • Ting Li
    Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Yongjing Cheng
    Department of Rheumatology and Immunology, Beijing Hospital, National Centre of Gerontology, Beijing, China.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals