0
Article Tier 2 Detection Methods Sign in to save

Automated Particle Analysis in Image J

AI summary Read the abstract

This methodological paper described automated particle analysis techniques using ImageJ software for quantifying microplastics in environmental samples, providing guidance on image processing workflows. Automation of particle counting and measurement is important for processing the large sample volumes needed for comprehensive environmental monitoring.

This is a tutorial development for automating the particle size, shape, and color quantification with a use case of microplastic particles.

More Papers Like This

Article Tier 2

Automatic Counting and Classification of Microplastic Particles

AI summary Read the abstract

Researchers developed an automatic system for counting and classifying microplastic particles in marine samples, applying image analysis techniques to address the growing problem of plastic debris entering the food chain via marine species ingestion.

Article Tier 2

Microplastic and nanoplastic analysis methods, tests and reference materials

AI summary Read the abstract

Researchers described a workflow combining a streamlined experimental setup with automated image analysis to quantify marine microplastic debris, addressing the limitations of labor-intensive manual counting methods that currently prevent scalable and consistent global plastic monitoring.

Article Tier 2

A Machine Learning Approach To Microplastic Detection And Quantification In Aquatic Environments

AI summary Read the abstract

This study developed a machine learning approach for detecting and quantifying microplastics in aquatic environments, demonstrating that automated image analysis can improve throughput and accuracy compared to manual microscopic counting for environmental monitoring applications.

Article Tier 2

Image processing techniques for measuring primary microplastic abundance in various of dispersant

AI summary Read the abstract

Researchers developed an image processing technique (IPT) using ImageJ software combined with various dispersants to quantify primary microplastic (microbead) abundance directly in liquid samples without prior extraction. They found a strong correlation (R2 > 0.75) between sample mass and particle count and achieved limits of detection of 1.75 particles for polypropylene and 0.00009 for polyethylene, offering a lower-cost alternative to conventional microscopy for microplastic quantification.

Article Tier 2

An Image-Processing Tool for Size and Shape Analysis of Manufactured Irregular Polyethylene Microparticles

AI summary Read the abstract

Scientists developed a free, automated image-processing tool that can quickly analyze microscope images to count and measure irregularly shaped microplastic particles, calculating their size, shape, and distribution. Traditional methods require manually counting particles under a microscope, which is slow and impractical for large samples. Better tools for measuring microplastic contamination help researchers more accurately assess how much plastic pollution exists in water and soil that affects human exposure.

Research digests by email

When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.

Email me about

Share this paper