In this repository we analyse pairs of microscopic images containing bright particles on dark background. The code was created for a study developing an evaluation concept for microplastic purification protocols.
The original publication can be found here: Measuring impacts of microplastic treatments via image recognition on immobilised particles below 100 μm. Micropl.&Nanopl. 1, 12 (2021)
Microplastic particles are immobilised on a plane silicon wafer substrate using a micrometre thin spin coated layer of epoxy resin. After curing, the wafer is imaged, exposed to a treatment that needs evaluation and subsequently imaged again. The pre- and post-treatment images are compared with respect to changes in particle areas and numbers caused by the treatment.
There are two main parts in the analysis of the image:
- identifying, matching and measuring particles
- evaluating and plotting the results
The first part is started by running the compareDigestImages.py where appropriate paths to the pre-post-image directories need to be entered.
To replicate the original study's analysis, all required image data can be obtained from: DOI: 10.5281/zenodo.4568489.
A wafer-polymer-keyfile.csv is needed to map file names to polymers and should be placed in the main directory where the code is run. The original keyfile is included as an example in this repo and also with the deposited images.
When the measurements finish, all results are saved in a set of csv files which contain the data of the particle measurements.
In the second part these result csv files are read by running the analyse_data.py in the data_analysis subdirectory.
Finally, the results are visualised for further exploration in an interactive figure (based on the Altair python library) and saved as an html file.
The output figure used in the original publication can be found at: DOI: 10.5281/zenodo.4568525.