AI-based techniques in sperm detection

PURPOSE OF REVIEW: Artificial intelligence (AI) is emerging as a promising tool for sperm detection in men with azoospermia and cryptozoospermia, conditions in which rare spermatozoa can be difficult and time-consuming to identify. This review summarizes recent advances in AI-assisted sperm detection and their potential clinical applications. RECENT FINDINGS: Recent studies demonstrate that deep learning-based systems can improve the speed and sensitivity of sperm detection in both testicular tissue and ejaculate samples. AI-assisted image analysis has reduced search times and improved detection rates compared with conventional manual evaluation. Emerging technologies include augmented reality platforms that support embryologists during sperm searches and AI-integrated microfluidic systems capable of sperm detection and isolation. Early clinical data suggest these approaches may enable sperm recovery in patients previously considered sperm-negative by conventional methods. SUMMARY: AI-assisted sperm detection has the potential to improve efficiency, reproducibility, and access to fertility treatment for men with severe male factor infertility. Although further validation is required, ongoing advances in AI, imaging, and microfluidics may transform the diagnosis and management of azoospermia and cryptozoospermia.

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Publication Details

Journal
Current Opinion in Urology
Published
2026-07-17
DOI
https://doi.org/10.1097/mou.0000000000001430
Primary Topic
Sperm and Testicular Function
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-based techniques in sperm detection

Hemant Suryawanshi, Laura C. Gemmell, Zev Williams
Current Opinion in Urology
Sperm and Testicular Function
article

AI-based techniques in sperm detection

Hemant Suryawanshi, Laura C. Gemmell, Zev Williams
article en

Abstract

PURPOSE OF REVIEW: Artificial intelligence (AI) is emerging as a promising tool for sperm detection in men with azoospermia and cryptozoospermia, conditions in which rare spermatozoa can be difficult and time-consuming to identify. This review summarizes recent advances in AI-assisted sperm detection and their potential clinical applications. RECENT FINDINGS: Recent studies demonstrate that deep learning-based systems can improve the speed and sensitivity of sperm detection in both testicular tissue and ejaculate samples. AI-assisted image analysis has reduced search times and improved detection rates compared with conventional manual evaluation. Emerging technologies include augmented reality platforms that support embryologists during sperm searches and AI-integrated microfluidic systems capable of sperm detection and isolation. Early clinical data suggest these approaches may enable sperm recovery in patients previously considered sperm-negative by conventional methods. SUMMARY: AI-assisted sperm detection has the potential to improve efficiency, reproducibility, and access to fertility treatment for men with severe male factor infertility. Although further validation is required, ongoing advances in AI, imaging, and microfluidics may transform the diagnosis and management of azoospermia and cryptozoospermia.

Current Opinion in Urology
Columbia University Irving Medical Center (US)
Openalex Percentile: Top 7%
Sperm and Testicular Function
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