Hyperspectral microscopy as a particle exposure assessment tool

Carolina Blanch-Perez del Notario; Pieter Bertier; Murali Jayapala; Andy Lambrechts

doi:10.1117/12.3002829

12 March 2024 Hyperspectral microscopy as a particle exposure assessment tool

Carolina Blanch-Perez del Notario, Pieter Bertier, Murali Jayapala, Andy Lambrechts

Proceedings Volume 12848, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXXI; 1284803 (2024) https://doi.org/10.1117/12.3002829
Event: SPIE BiOS, 2024, San Francisco, California, United States

Abstract

Hyperspectral imaging combines the characteristics of computer vision and point spectroscopy by obtaining an image with both spatial and spectral information. Therefore, in combination with microscopy, it can increase material discrimination possibilities with respect to regular microscopy imaging. We explore this increased discrimination potential to assess exposure to particle contamination, since workplace exposure to specific particle materials poses well-known health hazards. In this respect, we are focusing on discriminating more health relevant particles such as silica in the respirable size fraction. For this purpose, a particle sampling protocol has been proposed and hyperspectral imaging in combination with transmission microscopy is used for particle material identification. We use a Snapscan visual near-infrared (VNIR) camera providing high spectral and spatial resolution in the 460-900 nm range, 150 spectral bands and up to 7 Mpixels of spatial resolution and high acquisition speed. The hyperspectral microscopy system has been tested for discrimination of fifteen different particle materials, such as silica, coal, dolomite, barite, or rutile, among others. The combined analysis of spatial and spectral information shows potential to accurately discriminate the 15 tested particle materials so far by means of a random forest classifier. In addition, a band relevance analysis is performed showing that only a few specific bands are needed to provide accurate discrimination of the tested materials. The hyperspectral hardware and method presented could lead to a faster exposure assessment than traditional techniques used for occupational exposure estimation.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Carolina Blanch-Perez del Notario, Pieter Bertier, Murali Jayapala, and Andy Lambrechts "Hyperspectral microscopy as a particle exposure assessment tool", Proc. SPIE 12848, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXXI, 1284803 (12 March 2024); https://doi.org/10.1117/12.3002829

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