Deep learning-based automated guide for defining a standard imaging plane for developmental dysplasia of the hip screening using ultrasonography: a retrospective imaging analysis
Our deep-learning network model is feasible for detecting five landmarks for DDH using ultrasound images. The primary parameters to determine DDH will be significantly detected by applying the deep-learning model in clinical settings.
Authors
- Ji Hye Choi (ORCID: https://orcid.org/0000-0002-0062-4222)
- Hyuk Pyo Kwon
- Seo Yeon Lee (ORCID: https://orcid.org/0000-0003-2585-7863)
- Kyung‐Sik Ahn (ORCID: https://orcid.org/0000-0001-9354-5699)
- Yongwon Cho
- Woo Young Jang (ORCID: https://orcid.org/0000-0003-1775-7715)
Institutions
- Korea University (KR)
- Soonchunhyang University (KR)
- Korea University Medical Center (KR)
- Korea University (JP)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2025-02-18
- DOI
- https://doi.org/10.1186/s12911-025-02926-8
- Citations
- 1
- Primary Topic
- Hip disorders and treatments
- Type
- article
- Field-Weighted Citation Impact
- 2.01
Funders
- Korea Medical Device Development Fund
- National Research Foundation
- Korea University
- Ministry of Trade, Industry and Energy
- Ministry of Food and Drug Safety
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea
- Korea University Anam Hospital