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Leveraging synthetic imagery and YOLOv8 for a novel colorimetric approach to paper-based point-of-care male fertility testing   
Yazarlar (9)
Olgac Özarslan
Koç Üniversitesi, Türkiye
Begum Kubra Tokyay
Koç Üniversitesi, Türkiye
Cansu Soylemez
Koç Üniversitesi, Türkiye
Mehmet Tugrul Birtek
Koç Üniversitesi, Türkiye
Doç. Dr. Zihni Onur UYGUN Doç. Dr. Zihni Onur UYGUN
Kafkas Üniversitesi, Türkiye
İpek Keles
Koç Üniversitesi, Türkiye
Begum Aydogan Mathyk
Morsani College of Medicine, United States
Cihan Halicigil
Yale School of Medicine, United States
Savas Tasoglu
Koç Üniversitesi, Türkiye
Devamını Göster
Özet
The development of paper-based systems has revolutionized point-of-care (POC) applications by enabling rapid, robust, accurate and sensitive biochemical analysis, infectious disease diagnosis, and fertility monitoring, in particular, in male fertility monitoring, offering portable, cost-effective solutions compared to traditional methods. This innovation addresses high costs and limited accessibility of male fertility testing in resource-poor settings. Male infertility, a significant issue globally, often faces stigma, hindering men from seeking care. This study introduces a novel approach to male fertility testing using colorimetric analysis of paper-based assays, enhanced by synthetic imagery and the YOLOv8 (You Only Look Once) object detection algorithm. Synthetic imagery was employed to train and fine-tune YOLOv8, enhancing its capability to accurately detect color changes in paper-based tests. This colorimetric detection leverages smartphone imaging, making it both accessible and scalable. Initial experiments demonstrate that YOLOv8’s precision and efficiency, when combined with synthetic data, significantly enhance the system's ability to recognize and analyze colorimetric signals, positioning it as a promising tool for male fertility POC diagnostics. In our study, we evaluated 39 semen samples for pH and sperm count using standard clinical tests, comparing these results with a novel paper-based semen analysis kit. This kit utilizes reaction zones that exhibit color changes when exposed to semen samples, with images captured using a smartphone under varied lighting conditions. Despite a limited number of images, our synthetically trained YOLOv8 model achieved an accuracy of 0.86, highlighting its potential to improve the reliability of colorimetric analysis for both home and clinical use.
Anahtar Kelimeler
Makale Türü Özgün Makale
Makale Alt Türü ESCI dergilerinde yayımlanan tam makale
Dergi Adı Sensors and Diagnostics
Dergi ISSN 2635-0998
Makale Dili İngilizce
Basım Tarihi 01-2025
Cilt No 4
Sayı 1
Sayfalar 336 / 344
Doi Numarası 10.1039/d4sd00348a