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Nanoparticle Detection on SEM Images Using a Neural Network and Semi-Synthetic Training Data

Processing images represents a necessary step in the process of analysing the information gathered about nanoparticles after characteristic material samples have been scanned with electron microscopy, which often requires the use of image processing techniques or general purpose image manipulation s...

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Autores principales: López Gutiérrez, Jorge David, Abundez Barrera, Itzel Maria, Torres Gómez, Nayely
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9182493/
https://www.ncbi.nlm.nih.gov/pubmed/35683674
http://dx.doi.org/10.3390/nano12111818
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author López Gutiérrez, Jorge David
Abundez Barrera, Itzel Maria
Torres Gómez, Nayely
author_facet López Gutiérrez, Jorge David
Abundez Barrera, Itzel Maria
Torres Gómez, Nayely
author_sort López Gutiérrez, Jorge David
collection PubMed
description Processing images represents a necessary step in the process of analysing the information gathered about nanoparticles after characteristic material samples have been scanned with electron microscopy, which often requires the use of image processing techniques or general purpose image manipulation software to carry out tasks such as nanoparticle detection and measurement. In recent years, the use of networks has been successfully implemented to detect and classify electron microscopy images as well as the objects within them. In this work, we present four detection models using two versions of the YOLO neural network architectures trained to detect cubical and quasi-spherical particles in SEM images; the training datasets are a mixture of real images and synthetic ones generated by a semi-arbitrary method. The resulting models were capable of detecting nanoparticles in images different than the ones used for training and identifying them in some cases as the close proximity between nanoparticles proved a challenge for the neural networks in most situations.
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spelling pubmed-91824932022-06-10 Nanoparticle Detection on SEM Images Using a Neural Network and Semi-Synthetic Training Data López Gutiérrez, Jorge David Abundez Barrera, Itzel Maria Torres Gómez, Nayely Nanomaterials (Basel) Article Processing images represents a necessary step in the process of analysing the information gathered about nanoparticles after characteristic material samples have been scanned with electron microscopy, which often requires the use of image processing techniques or general purpose image manipulation software to carry out tasks such as nanoparticle detection and measurement. In recent years, the use of networks has been successfully implemented to detect and classify electron microscopy images as well as the objects within them. In this work, we present four detection models using two versions of the YOLO neural network architectures trained to detect cubical and quasi-spherical particles in SEM images; the training datasets are a mixture of real images and synthetic ones generated by a semi-arbitrary method. The resulting models were capable of detecting nanoparticles in images different than the ones used for training and identifying them in some cases as the close proximity between nanoparticles proved a challenge for the neural networks in most situations. MDPI 2022-05-26 /pmc/articles/PMC9182493/ /pubmed/35683674 http://dx.doi.org/10.3390/nano12111818 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
López Gutiérrez, Jorge David
Abundez Barrera, Itzel Maria
Torres Gómez, Nayely
Nanoparticle Detection on SEM Images Using a Neural Network and Semi-Synthetic Training Data
title Nanoparticle Detection on SEM Images Using a Neural Network and Semi-Synthetic Training Data
title_full Nanoparticle Detection on SEM Images Using a Neural Network and Semi-Synthetic Training Data
title_fullStr Nanoparticle Detection on SEM Images Using a Neural Network and Semi-Synthetic Training Data
title_full_unstemmed Nanoparticle Detection on SEM Images Using a Neural Network and Semi-Synthetic Training Data
title_short Nanoparticle Detection on SEM Images Using a Neural Network and Semi-Synthetic Training Data
title_sort nanoparticle detection on sem images using a neural network and semi-synthetic training data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9182493/
https://www.ncbi.nlm.nih.gov/pubmed/35683674
http://dx.doi.org/10.3390/nano12111818
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