Application of artificial intelligence in the analysis of asbestos fibers
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...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-07-01
|
| Series: | Frontiers in Public Health |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1584136/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849415617758625792 |
|---|---|
| author | Richard Lee Drew Van Orden Suzanne Blanda John Mihalick David Bickford Patrick Metsch |
| author_facet | Richard Lee Drew Van Orden Suzanne Blanda John Mihalick David Bickford Patrick Metsch |
| author_sort | Richard Lee |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-5ea18edca532403fafb13359a6e3dcfa |
| institution | Kabale University |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj-art-5ea18edca532403fafb13359a6e3dcfa2025-08-20T03:33:27ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-07-011310.3389/fpubh.2025.15841361584136Application of artificial intelligence in the analysis of asbestos fibersRichard Lee0Drew Van Orden1Suzanne Blanda2John Mihalick3David Bickford4Patrick Metsch5RJ Lee Group, Inc., Pittsburgh, PA, United StatesConsultant, Trafford, PA, United StatesRJ Lee Group, Inc., Pittsburgh, PA, United StatesRJ Lee Group, Inc., Pittsburgh, PA, United StatesRJ Lee Group, Inc., Pittsburgh, PA, United StatesRJ Lee Group, Inc., Pittsburgh, PA, United StatesAutomated 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.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1584136/fullasbestosautomationidentificationartificial intelligenceamphibole |
| spellingShingle | Richard Lee Drew Van Orden Suzanne Blanda John Mihalick David Bickford Patrick Metsch Application of artificial intelligence in the analysis of asbestos fibers Frontiers in Public Health asbestos automation identification artificial intelligence amphibole |
| title | Application of artificial intelligence in the analysis of asbestos fibers |
| title_full | Application of artificial intelligence in the analysis of asbestos fibers |
| title_fullStr | Application of artificial intelligence in the analysis of asbestos fibers |
| title_full_unstemmed | Application of artificial intelligence in the analysis of asbestos fibers |
| title_short | Application of artificial intelligence in the analysis of asbestos fibers |
| title_sort | application of artificial intelligence in the analysis of asbestos fibers |
| topic | asbestos automation identification artificial intelligence amphibole |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1584136/full |
| work_keys_str_mv | AT richardlee applicationofartificialintelligenceintheanalysisofasbestosfibers AT drewvanorden applicationofartificialintelligenceintheanalysisofasbestosfibers AT suzanneblanda applicationofartificialintelligenceintheanalysisofasbestosfibers AT johnmihalick applicationofartificialintelligenceintheanalysisofasbestosfibers AT davidbickford applicationofartificialintelligenceintheanalysisofasbestosfibers AT patrickmetsch applicationofartificialintelligenceintheanalysisofasbestosfibers |