Accurate Acupoint Localization in 2D Hand Images: Evaluating HRNet and ResNet Architectures for Enhanced Detection Performance
HRNet's superior performance in acupoint localization suggests its potential to improve the precision and efficacy of acupuncture treatments. The study highlights the promising role of machine learning in enhancing traditional medical practices and underscores the importance of accurate acupoint localization in clinical acupuncture.
Authors
- Myunggi Yi (ORCID: https://orcid.org/0000-0003-4864-959X)
- Byeong-Il Lee (ORCID: https://orcid.org/0000-0002-1574-7145)
- Nuwan Madusanka (ORCID: https://orcid.org/0000-0001-7982-1036)
- Hadi Sedigh Malekroodi (ORCID: https://orcid.org/0009-0001-1958-1525)
- Seon-Deok Seo
- Chang-Soo Na
Institutions
- Dongshin University (KR)
- Pukyong National University (KR)
Publication Details
- Journal
- Current Medical Imaging Formerly Current Medical Imaging Reviews
- Published
- 2024-11-06
- DOI
- https://doi.org/10.2174/0115734056315235240820080406
- Citations
- 8
- Primary Topic
- Medical Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.48
Funders
- National Research Foundation of Korea