Application of artificial intelligence in the analysis of asbestos fibers - Richard Lee; Drew Van Orden; Suzanne Blanda; John Mihalick; David Bickford; Patrick Metsch (Frontiers in Public Health, 2025)
Automated asbestos fiber detection and identification has been the goal of asbestos microscopists for decades. The advent of inexpensive memory, fast digital processing, machine learning, and microscope automation provide the enabling platform for success. This paper will review recent developments in fiber detection and identification by PCM and SEM and will present recent progress in employing artificial intelligence in the TEM classification of asbestos and non-asbestos amphiboles in the evaluation of elongated minerals in raw materials. To date, this project has been self-funded.