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

Keiya Sugiura; Toshio Ogawa; Yoshitaka Adachi; Fei Sun; Asuka Suzuki; Akinori Yamanaka; Nobuo Nakada; Takuya Ishimoto; Takayoshi Nakano; Yuichiro Koizumi

doi:10.3390/jimaging9050090

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

Keiya Sugiura, Toshio Ogawa, Yoshitaka Adachi^*, Fei Sun, Asuka Suzuki, Akinori Yamanaka, Nobuo Nakada, Takuya Ishimoto, Takayoshi Nakano, Yuichiro Koizumi

^*この論文の責任著者

先進軽金属材料国際研究機構先進アルミニウム国際研究センター

研究成果: ジャーナルへの寄稿 › 学術論文 › 査読

7 被引用数 (Scopus)

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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.

本文言語	英語
論文番号	90
ジャーナル	Journal of Imaging
巻	9
号	5
DOI	https://doi.org/10.3390/jimaging9050090
出版ステータス	出版済み - 2023/05

ASJC Scopus 主題領域

放射線学、核医学およびイメージング
コンピュータビジョンおよびパターン認識
コンピュータグラフィックスおよびコンピュータ支援設計
電子工学および電気工学

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10.3390/jimaging9050090

引用スタイル

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

abstract = "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.",

keywords = "SliceGAN, additive manufacturing, autocorrelation function, generative adversarial network, synthetic 3D image",

author = "Keiya Sugiura and Toshio Ogawa and Yoshitaka Adachi and Fei Sun and Asuka Suzuki and Akinori Yamanaka and Nobuo Nakada and Takuya Ishimoto and Takayoshi Nakano and Yuichiro Koizumi",

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doi = "10.3390/jimaging9050090",

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T1 - Big-Volume SliceGAN for Improving a Synthetic 3D Microstructure Image of Additive-Manufactured TYPE 316L Steel

AU - Sugiura, Keiya

AU - Ogawa, Toshio

AU - Adachi, Yoshitaka

AU - Sun, Fei

AU - Suzuki, Asuka

AU - Yamanaka, Akinori

AU - Nakada, Nobuo

AU - Ishimoto, Takuya

AU - Nakano, Takayoshi

AU - Koizumi, Yuichiro

PY - 2023/5

Y1 - 2023/5

N2 - 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.

AB - 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.

KW - SliceGAN

KW - additive manufacturing

KW - autocorrelation function

KW - generative adversarial network

KW - synthetic 3D image

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DO - 10.3390/jimaging9050090

M3 - 学術論文

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

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ASJC Scopus 主題領域

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