Neoplasms in the Nasal Cavity Identified and Tracked with an Artificial Intelligence-Assisted Nasal Endoscopic Diagnostic System
This study successfully established an AI-assisted nasal endoscopic diagnostic system that can preliminarily identify nasal neoplasms from endoscopic images and automatically track them in real time during surgery, enhancing the efficiency of endoscopic diagnosis and surgery.
Authors
- Xiayue Xu
- Shaoqing Yu (ORCID: https://orcid.org/0000-0003-2208-4535)
- Ling Jin (ORCID: https://orcid.org/0000-0001-9867-385X)
- Yumin Zhao (ORCID: https://orcid.org/0000-0002-6573-7551)
- Shiwang Tan
- Boxiang Yun (ORCID: https://orcid.org/0000-0003-2233-6691)
- Xiaolin Zhang (ORCID: https://orcid.org/0000-0002-4112-4873)
- Chuanliang Zhao (ORCID: https://orcid.org/0000-0002-9625-9329)
- Qingli Li (ORCID: https://orcid.org/0000-0001-5063-8801)
- Yan Wang (ORCID: https://orcid.org/0000-0002-5344-1884)
- Kai Fan
- Zimu Zhang (ORCID: https://orcid.org/0000-0003-0415-9425)
- Yi Zong (ORCID: https://orcid.org/0000-0003-1262-3558)
- Guanzhen Yu
Institutions
- Tongji University (CN)
- Tongji Hospital (CN)
- East China Normal University (CN)
Publication Details
- Journal
- Bioengineering
- Published
- 2024-12-25
- DOI
- https://doi.org/10.3390/bioengineering12010010
- Citations
- 2
- Primary Topic
- Nasal Surgery and Airway Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.15
Funders
- National Science Foundation
- Tongji University
- Shanghai Hospital Development Center
- National Key Research and Development Program of China