Deep learning-based automated guide for defining a standard imaging plane for developmental dysplasia of the hip screening using ultrasonography: a retrospective imaging analysis.

Journal: BMC medical informatics and decision making
PMID: 39966904

Abstract

BACKGROUND: We aimed to propose a deep-learning neural network model for automatically detecting five landmarks during a two-dimensional (2D) ultrasonography (US) scan to develop a standard plane for developmental dysplasia of the hip (DDH) screening.

Authors

  • Kyung-Sik Ahn
    Department of Radiology, Korea University Anam Hospital, Seoul, Korea.
  • Ji Hye Choi
    Department of Orthopedic Surgery, Korea University Anam Hospital, 73, Goryeodae-ro, Seoungbuk-gu, Seoul, 02841, Republic of Korea.
  • Heejou Kwon
    LG Electronics, 19, Yangjae-daero 11-gil, Seocho-gu, Seoul, Republic of Korea.
  • Seoyeon Lee
    Department of Biomedical Engineering, Korea University, Goryeodae-ro, Seoungbuk-gu, Seoul, 02841, Republic of Korea.
  • Yongwon Cho
    Department of Convergence Medicine, Asan Medical Center, College of Medicine, University of Ulsan, 88, Olympic-ro 43-gil, Seoul, 05505, South Korea.
  • Woo Young Jang
    Department of Orthopedic Surgery, Korea University Anam Hospital, 73, Goryeodae-ro, Seoungbuk-gu, Seoul, 02841, Republic of Korea. opmanse@korea.ac.kr.

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