Automatic identification of human spermatozoa with zona pellucida-binding capability using deep learning
This study was supported in part by two Health and Medical Research Funds, the Food and Health Bureau, The Government of the HKSAR (07182446 and 11222236), and the Sanming Project of Medicine in Shenzhen (SZSM 202211014). Two provisional patent applications related to the data presented here have been filed on behalf of The University of Hong Kong (i. application no. 63/511,375; filing date: 30 June 2023; current status: active; applicant: The University of Hong Kong; ii. application no. US 63/567,147; filing date: 19 March 2024; current status: active; applicant: The University of Hong Kong). The authors declare that they have no other competing interests.
Authors
- Erica T. Y. Leung (ORCID: https://orcid.org/0000-0003-0510-6309)
- Raymond Li (ORCID: https://orcid.org/0000-0002-7957-7798)
- Lequan Yu (ORCID: https://orcid.org/0000-0002-9315-6527)
- Ernest Hung Yu Ng (ORCID: https://orcid.org/0000-0002-7688-4557)
- Kevin K.W. Lam (ORCID: https://orcid.org/0000-0001-9385-4846)
- Philip C.N. Chiu (ORCID: https://orcid.org/0000-0001-6217-1970)
- Cheuk‐Lun Lee (ORCID: https://orcid.org/0000-0003-1553-3478)
- Brayden K. M. Lee
- Xianghan Mei
- William S.B. Yeung (ORCID: https://orcid.org/0000-0003-0670-0879)
Institutions
- Hong Kong Polytechnic University (HK)
- Chinese University of Hong Kong (HK)
- Queen Mary Hospital (CN)
- University of Hong Kong - Shenzhen Hospital (CN)
- University of Hong Kong (HK)
Publication Details
- Journal
- Human Reproduction Open
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1093/hropen/hoaf024
- Citations
- 4
- Primary Topic
- Sperm and Testicular Function
- Type
- article
- Field-Weighted Citation Impact
- 6.79