uFTIR_curated Computer Vision Project

Micro-FTIR Filter Images for Particle Detection

This dataset consists of annotated images of filters containing particles. The primary objective of this dataset is to serve as training and validation data for developing a particle detection model using computer vision techniques. More specifically, this dataset can be used to train an image segmentation model that can be used with GEPARD (https://pubmed.ncbi.nlm.nih.gov/32436395/) in order to perform efficient particle detection and analysis using Micro-FTIR microscope.

Two kind of samples are used in our case:

• Normal filters, with a low amount of particles and a clear view of the filter
• Saturated filters, where the particles cover almost all the filter

In the first case, particles were annotated easilly as they are clearly visible over the filter. In the second scenario, the most distinguishable particles on the image have been annotated.

Note

In the case of a saturated filters, the correct method would be to collect a spectral image of the entire filter using a FPA detector or similar and then use tools (e.g. sIMPle ) to analyse this image. However, in our scenario such detector was not available, and a semi-random / operator dependant method had to be used in order to select particles or points for scanning.