Research data for Microplastic quantification in food samples, using stereomicroscopy and smartphone camera, leveraging interactive supervised machine learning tools - JPCE

Research data for the article "Microplastic quantification in food samples, using stereomicroscopy and smartphone camera, leveraging interactive supervised machine learning tools". This repository contains the datasets and processing files used in the microplastic detection workflow developed in this study. The files included allow reproducibility of the image analysis pipeline. The repository contains: (i) raw microscopy images (.png) corresponding to the validation dataset used to evaluate the trained models; (ii) trained Ilastik project files (.ilp) for the two classifiers developed in this work (filament and fragment detection), which can be opened directly in the Ilastik software* to reproduce the image probability segmentation step; and (iii) FIJI macros (.ijm) used for image preprocessing and automated particle analysis in Fiji.