# Application of artificial intelligence in the analysis of asbestos fibers

## TL;DR

This paper explores how artificial intelligence can help detect and identify asbestos fibers using advanced microscopy techniques.

## Contribution

The paper presents recent progress in using artificial intelligence for TEM classification of asbestos and non-asbestos amphiboles.

## Key findings

- AI is being applied to improve the classification of asbestos fibers in transmission electron microscopy.
- Recent developments in PCM and SEM have enhanced fiber detection capabilities.
- The project has been self-funded, indicating independent innovation in the field.

## Abstract

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.