Augmentation method for convolutional neural network that improves prediction performance in the task of classifying primary lung cancer and lung metastasis using CT images

Takuma Usuzaki; Kengo Takahashi; Kazuma Umemiya; Mami Ishikuro; Taku Obara; Masahiro Kamimoto; Kazuhiro Majima

doi:10.1016/j.lungcan.2021.06.021

Augmentation method for convolutional neural network that improves prediction performance in the task of classifying primary lung cancer and lung metastasis using CT images

Takuma Usuzaki, Kengo Takahashi, Kazuma Umemiya, Mami Ishikuro, Taku Obara, Masahiro Kamimoto, Kazuhiro Majima

東北メディカル・メガバンク機構

研究成果: ジャーナルへの寄稿 › レター › 査読

5 被引用数 (Scopus)

本文言語	英語
ページ（範囲）	175-178
ページ数	4
ジャーナル	Lung Cancer
巻	160
DOI	https://doi.org/10.1016/j.lungcan.2021.06.021
出版ステータス	出版済み - 2021 10月

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この成果は、次の持続可能な開発目標に貢献しています

文献へのアクセス

10.1016/j.lungcan.2021.06.021

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引用スタイル

@article{b7da9f38c303425fbb9b48a5534508d2,

title = "Augmentation method for convolutional neural network that improves prediction performance in the task of classifying primary lung cancer and lung metastasis using CT images",

keywords = "Deep learning, Lung cancer, Lung nodule",

author = "Takuma Usuzaki and Kengo Takahashi and Kazuma Umemiya and Mami Ishikuro and Taku Obara and Masahiro Kamimoto and Kazuhiro Majima",

note = "Funding Information: The authors acknowledge the National Cancer Institute and the Foundation for the National Institutes of Health, and their critical role in the creation of the free publicly available LIDC/IDRI database used in this study. Data used in this research were obtained from The Cancer Imaging Archive (TCIA) sponsored by the Cancer Imaging Program, DCTD/NCI/NIH, https://wiki.cancerimagingarchive.net/display/Public/LIDC-IDRI.",

year = "2021",

month = oct,

doi = "10.1016/j.lungcan.2021.06.021",

language = "English",

volume = "160",

pages = "175--178",

journal = "Lung Cancer",

issn = "0169-5002",

publisher = "Elsevier Ireland Ltd",

}

TY - JOUR

T1 - Augmentation method for convolutional neural network that improves prediction performance in the task of classifying primary lung cancer and lung metastasis using CT images

AU - Usuzaki, Takuma

AU - Takahashi, Kengo

AU - Umemiya, Kazuma

AU - Ishikuro, Mami

AU - Obara, Taku

AU - Kamimoto, Masahiro

AU - Majima, Kazuhiro

N1 - Funding Information: The authors acknowledge the National Cancer Institute and the Foundation for the National Institutes of Health, and their critical role in the creation of the free publicly available LIDC/IDRI database used in this study. Data used in this research were obtained from The Cancer Imaging Archive (TCIA) sponsored by the Cancer Imaging Program, DCTD/NCI/NIH, https://wiki.cancerimagingarchive.net/display/Public/LIDC-IDRI.

PY - 2021/10

Y1 - 2021/10

KW - Deep learning

KW - Lung cancer

KW - Lung nodule

UR - http://www.scopus.com/inward/record.url?scp=85111528437&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85111528437&partnerID=8YFLogxK

U2 - 10.1016/j.lungcan.2021.06.021

DO - 10.1016/j.lungcan.2021.06.021

M3 - Letter

C2 - 34303540

AN - SCOPUS:85111528437

SN - 0169-5002

VL - 160

SP - 175

EP - 178

JO - Lung Cancer

JF - Lung Cancer

ER -