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Updated: Sep 14, 2025

Artificial Intelligence Approaches to Assessing Primary Cilia
Published on: May 1, 2021
Application of artificial intelligence in the analysis of asbestos fibers
Richard Lee1, Drew Van Orden2, Suzanne Blanda1
1RJ Lee Group, Inc., Pittsburgh, PA, United States.
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.
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