Deep-learning-based endoscopic single-shot fringe projection profilometry
A deep-learning-based single-shot FPP endoscopic system was shown to be highly effective in real-time depth map generation with millimeter-scale error. Implementing such a system has the potential to improve the reliability of image-guided robotic surgery.
Authors
- Michael H. Hsieh (ORCID: https://orcid.org/0000-0002-9650-2691)
- Axel Krieger (ORCID: https://orcid.org/0000-0001-8169-075X)
- Ruichen Huang
- Shuwen Wei (ORCID: https://orcid.org/0000-0001-8679-9615)
- Waymond Rodgers (ORCID: https://orcid.org/0000-0003-4349-5667)
- Jinglun Yu (ORCID: https://orcid.org/0000-0001-9541-5943)
- Ruizhi Zuo (ORCID: https://orcid.org/0000-0002-0464-6234)
- Yaning Wang (ORCID: https://orcid.org/0000-0001-6258-8063)
- Jin U. Kang (ORCID: https://orcid.org/0000-0001-5817-1935)
Institutions
- Children's National (US)
- Johns Hopkins University (US)
- Johns Hopkins Medicine (US)
Publication Details
- Journal
- Journal of Biomedical Optics
- Published
- 2025-08-19
- DOI
- https://doi.org/10.1117/1.jbo.30.8.086003
- Primary Topic
- Optical measurement and interference techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health