Year: 2026
Type: article
Abstract: This paper presents a semi-autonomous AI-based platform designed for the efficient management and quantitative analysis of human spermatozoa. Addressing the limitations of manual semen analysis, this system integrates advanced image processing and analytical techniques to offer a high-throughput diagnostic solution. During operation, the proposed system autonomously performs a precise quantitative assessment of sperm concentration, accurately tracks individual sperm motility patterns, and systematically classifies morphological abnormalities. The result is a comprehensive sperm analysis report, meticulously generated according to the latest established World Health Organization (WHO) guidelines for concentration, motility, and morphology. A distinguishing feature of this system is the ability to yield reliable preliminary results even with minimally pre-processed clinical samples, thereby enhancing diagnostic objectivity, efficiency, and reliability in male reproductive health assessments.
Source: Applied Sciences
DOI: 10.3390/app16021067
Authors: Son The Trinh, Nhat Ngoc Nguyen, Thanh Quoc Trinh, Viet Trinh
Language: English
Subfield: Reproductive Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W7124891064