Big-Volume SliceGAN for Improving a Synthetic 3D Microstructure Image of Additive-Manufactured TYPE 316L Steel

A modified SliceGAN architecture was proposed to generate a high-quality synthetic three-dimensional (3D) microstructure image of TYPE 316L material manufactured through additive methods. The quality of the resulting 3D image was evaluated using an auto-correlation function, and it was discovered th...

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Autores principales: Sugiura, Keiya, Ogawa, Toshio, Adachi, Yoshitaka, Sun, Fei, Suzuki, Asuka, Yamanaka, Akinori, Nakada, Nobuo, Ishimoto, Takuya, Nakano, Takayoshi, Koizumi, Yuichiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10218809/
https://www.ncbi.nlm.nih.gov/pubmed/37233310
http://dx.doi.org/10.3390/jimaging9050090
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author Sugiura, Keiya
Ogawa, Toshio
Adachi, Yoshitaka
Sun, Fei
Suzuki, Asuka
Yamanaka, Akinori
Nakada, Nobuo
Ishimoto, Takuya
Nakano, Takayoshi
Koizumi, Yuichiro
author_facet Sugiura, Keiya
Ogawa, Toshio
Adachi, Yoshitaka
Sun, Fei
Suzuki, Asuka
Yamanaka, Akinori
Nakada, Nobuo
Ishimoto, Takuya
Nakano, Takayoshi
Koizumi, Yuichiro
author_sort Sugiura, Keiya
collection PubMed
description A modified SliceGAN architecture was proposed to generate a high-quality synthetic three-dimensional (3D) microstructure image of TYPE 316L material manufactured through additive methods. The quality of the resulting 3D image was evaluated using an auto-correlation function, and it was discovered that maintaining a high resolution while doubling the training image size was crucial in creating a more realistic synthetic 3D image. To meet this requirement, modified 3D image generator and critic architecture was developed within the SliceGAN framework.
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spelling pubmed-102188092023-05-27 Big-Volume SliceGAN for Improving a Synthetic 3D Microstructure Image of Additive-Manufactured TYPE 316L Steel Sugiura, Keiya Ogawa, Toshio Adachi, Yoshitaka Sun, Fei Suzuki, Asuka Yamanaka, Akinori Nakada, Nobuo Ishimoto, Takuya Nakano, Takayoshi Koizumi, Yuichiro J Imaging Article A modified SliceGAN architecture was proposed to generate a high-quality synthetic three-dimensional (3D) microstructure image of TYPE 316L material manufactured through additive methods. The quality of the resulting 3D image was evaluated using an auto-correlation function, and it was discovered that maintaining a high resolution while doubling the training image size was crucial in creating a more realistic synthetic 3D image. To meet this requirement, modified 3D image generator and critic architecture was developed within the SliceGAN framework. MDPI 2023-04-29 /pmc/articles/PMC10218809/ /pubmed/37233310 http://dx.doi.org/10.3390/jimaging9050090 Text en © 2023 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
Sugiura, Keiya
Ogawa, Toshio
Adachi, Yoshitaka
Sun, Fei
Suzuki, Asuka
Yamanaka, Akinori
Nakada, Nobuo
Ishimoto, Takuya
Nakano, Takayoshi
Koizumi, Yuichiro
Big-Volume SliceGAN for Improving a Synthetic 3D Microstructure Image of Additive-Manufactured TYPE 316L Steel
title Big-Volume SliceGAN for Improving a Synthetic 3D Microstructure Image of Additive-Manufactured TYPE 316L Steel
title_full Big-Volume SliceGAN for Improving a Synthetic 3D Microstructure Image of Additive-Manufactured TYPE 316L Steel
title_fullStr Big-Volume SliceGAN for Improving a Synthetic 3D Microstructure Image of Additive-Manufactured TYPE 316L Steel
title_full_unstemmed Big-Volume SliceGAN for Improving a Synthetic 3D Microstructure Image of Additive-Manufactured TYPE 316L Steel
title_short Big-Volume SliceGAN for Improving a Synthetic 3D Microstructure Image of Additive-Manufactured TYPE 316L Steel
title_sort big-volume slicegan for improving a synthetic 3d microstructure image of additive-manufactured type 316l steel
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10218809/
https://www.ncbi.nlm.nih.gov/pubmed/37233310
http://dx.doi.org/10.3390/jimaging9050090
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