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A highly accurate and semi-automated method for quantifying spherical microplastics based on digital slide scanners and image processing

Environmental Research 2024 3 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Yu Tang, Yu Tang, Yu Tang, Yu Tang, Yu Tang, Yu Tang, Yu Tang, Yu Tang, Yu Tang, Yu Tang, Zhihui Hu, Jie Yao Jie Yao Jie Yao Yan Zhang, Yu Tang, Zekun Dong, Yu Tang, Yu Tang, Yu Tang, Yu Tang, Yu Tang, Yu Tang, Zekun Dong, Zekun Dong, Zekun Dong, Zekun Dong, Zekun Dong, Yu Tang, Zhihui Hu, Yu Tang, Yu Tang, Zhihui Hu, Zhihui Hu, Tongqing Wu, Tongqing Wu, Tongqing Wu, Tongqing Wu, Yu Tang, Tongqing Wu, Tongqing Wu, Yu Tang, Yu Tang, Yu Tang, Yan Zhang, Yu Tang, Jie Yao

Summary

Researchers developed a semi-automated image analysis system — combining a digital slide scanner with custom software — that can count and size spherical microplastics in water samples with less than 0.6% error, down to a minimum particle size of 1 micrometer. The system outperforms manual counting in speed and consistency, and was validated in both clean and polluted water. Accurate, high-throughput quantification tools like this are essential for producing reliable microplastic data that can be compared across laboratories and used to set health and environmental standards.

Microplastics (MPs), the emerging pollutants appeared in water environment, have grabbed significant attention from researchers. The quantitative method of spherical MPs is the premise and key for the study of MPs in laboratory researches. However, the manual counting is time-consuming, and the existing semi-automated analysis lacked of robustness. In this study, a highly accurate quantification method for spherical MPs, called VS120-MC was proposed. VS120-MC consisted of the digital slide scanner VS120 and the MPs image processing software, MPs-Counter. The full-area scanning photography was employed to fundamentally avoid the error caused by random or partition sampling modes. To accomplish high-performance batch recognition, the Weak-Circle Elimination Algorithm (WEA) and the Variable Coefficient Threshold (VCT) was developed. Finally, lower than 0.6% recognition error rate of simulated images with different aggregated indices was achieved by MPs-Counter with fast processing speed (about 2 s/image). The smallest size for VS120-MC to detect was 1 μm. And the applicability of VS120-MC in real water body was investigated. The measured value of 1 μm spherical MPs in ultra-pure water and two kinds of polluted water after digestion showed a good linear relationship with the Manual measurements (R = 0.982,0.987 and 0.978, respectively). For 10 μm spherical MPs, R reached 0.988 for ultra-pure water and 0.984 for both of the polluted water. MPs-Counter also showed robustness when using the same set of parameters processing the images with different conditions. Overall, VS120-MC eliminated the error caused by traditional photography and realized an accurate, efficient, stable image processing tool, providing a reliable alternative for the quantification of spherical MPs.

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