Lee Richard, Van Orden Drew, Blanda Suzanne, Mihalick John, Bickford David, Metsch Patrick
RJ Lee Group, Inc., Pittsburgh, PA, United States.
Consultant, Trafford, PA, United States.
Front Public Health. 2025 Jul 8;13:1584136. doi: 10.3389/fpubh.2025.1584136. eCollection 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.
几十年来,自动化石棉纤维检测与识别一直是石棉显微镜工作者的目标。廉价内存、快速数字处理、机器学习以及显微镜自动化的出现为成功提供了支持平台。本文将回顾通过相差显微镜(PCM)和扫描电子显微镜(SEM)进行纤维检测与识别的最新进展,并介绍在利用人工智能对原材料中细长矿物进行石棉和非石棉闪石的透射电子显微镜(TEM)分类方面取得的最新进展。迄今为止,该项目一直是自筹资金。