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Volume 28, Issue 2 (March 2026) 28, 166–172; 10.4103/aja202545
Integrated subcellular localization of functional fluorescence probes and functional analysis in motile spermatozoa by an AI-enhanced algorithm
Wei, Ya-Zhen1,2,*; Nong, Yu-Xiang3,*; Wu, Si-Xian1; Yang, Xiao-Xu4; Chen, Yu-Xi1,2; Yu, Kang-Kang5; Zhu, Han-Yu6; Shan, Xu-Dong7; Zhi, Wei-Wei8; Bian, Ang9; Xu, Wen-Ming1
1Joint Laboratory of Reproductive Medicine, Sichuan University-Chinese University of Hong Kong (SCU-CUHK), Key Laboratory of Obstetric, Gynaecologic and Paediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Med-X Centre for Manufacturing, Sichuan University, Chengdu 610041, China
2West China School of Pharmacy, Sichuan University, Chengdu 610041, China
3College of Software, Sichuan University, Chengdu 610065, China
4Department of Human Genetics, Utah Center for Genetic Discovery, University of Utah, Salt Lake City, UT 84112, USA
5Key Laboratory of Bio-Resources and Eco-Environment (Ministry of Education), College of Life Sciences, Sichuan University, Chengdu 610064, China
6Department of Computer and Information Science, University of Massachusetts Dartmouth, North Dartmouth, MA 02747, USA
7Reproductive Medicine Center, The Third People’s Hospital of Chengdu/The Affiliated Hospital of Southwest Jiao Tong University, Chengdu 610000, China
8Sichuan Provincial Maternity and Child Health Care Hospital, Chengdu 610000, China
9School of Computer and Software Engineering, Xihua University, Chengdu 610039, China
Correspondence: Dr. WM Xu (xuwenming@scu.edu.cn) or Dr. A Bian (bian@xhu.edu.cn)
Received: 13 March 2025; Accepted: 29 April 2025; published online: 05 September 2025
| Abstract |
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In the evaluation of male infertility, precise assessment of sperm functional competence has surpassed the requirements of conventional semen parameters. Existing computer-aided analysis systems are deficient at the molecular diagnostic level and also face challenges in live-cell fluorescence quantification. To address these issues, we have developed a novel integrated computational-imaging platform that combines a fine-tuned You Only Look Once version 8 (YOLOv8) architecture, tailored for the EVISEN dataset, with dual-probe fluorescence microscopy image segmentation, enabling simultaneous quantification of intracellular pH (pHi) and mitochondrial DNA G-quadruplexes (mtDNA G4s). By automating the localization of fluorescent foci, our algorithm systematically discriminates between the fluorescent signatures of the sperm head and principal piece, revealing correlations between fluorescence intensity ratios and sperm functional outcomes. This study demonstrates the potential of artificial intelligence (AI)-enhanced multimodal sperm analysis for molecular phenotyping of sperm functional competence. Integrating deep learning with live-cell fluorescence imaging, our platform offers a transformative tool for mechanistically informed diagnostics of male infertility.
Keywords: dual probe; EVISEN dataset; fluorescence imaging; YOLOv8
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