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  1. 原著論文

Super-resolution generative adversarial networks with static T2*WI-based subject-specific learning to improve spatial difference sensitivity in fMRI activation.

https://repo.qst.go.jp/records/86355
https://repo.qst.go.jp/records/86355
090213b7-17d6-40be-aebf-22878482dd36
Item type 学術雑誌論文 / Journal Article(1)
公開日 2022-06-20
タイトル
タイトル Super-resolution generative adversarial networks with static T2*WI-based subject-specific learning to improve spatial difference sensitivity in fMRI activation.
言語
言語 eng
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_6501
資源タイプ journal article
アクセス権
アクセス権 metadata only access
アクセス権URI http://purl.org/coar/access_right/c_14cb
著者 Junko, Ota

× Junko, Ota

WEKO 1052907

Junko, Ota

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Kensuke, Umehara

× Kensuke, Umehara

WEKO 1052908

Kensuke, Umehara

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Kershaw, Jeffrey

× Kershaw, Jeffrey

WEKO 1052909

Kershaw, Jeffrey

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Riwa, Kishimoto

× Riwa, Kishimoto

WEKO 1052910

Riwa, Kishimoto

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Yoshiyuki, Hirano

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WEKO 1052911

Yoshiyuki, Hirano

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Yasuhiko, Tachibana

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WEKO 1052912

Yasuhiko, Tachibana

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Hisateru, Ohba

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WEKO 1052913

Hisateru, Ohba

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Takayuki, Obata

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WEKO 1052914

Takayuki, Obata

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Junko, Ota

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WEKO 1052915

en Junko, Ota

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Kensuke, Umehara

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WEKO 1052916

en Kensuke, Umehara

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Kershaw, Jeffrey

× Kershaw, Jeffrey

WEKO 1052917

en Kershaw, Jeffrey

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Riwa, Kishimoto

× Riwa, Kishimoto

WEKO 1052918

en Riwa, Kishimoto

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Yoshiyuki, Hirano

× Yoshiyuki, Hirano

WEKO 1052919

en Yoshiyuki, Hirano

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Yasuhiko, Tachibana

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WEKO 1052920

en Yasuhiko, Tachibana

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Hisateru, Ohba

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WEKO 1052921

en Hisateru, Ohba

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Takayuki, Obata

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WEKO 1052922

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抄録
内容記述タイプ Abstract
内容記述 The spatial resolution of fMRI is relatively poor and improvements are needed to indicate more specific locations for functional activities. Here, we propose a novel scheme, called Static T2*WI-based Subject-Specific Super Resolution fMRI (STSS-SRfMRI), to enhance the functional resolution, or ability to discriminate spatially adjacent but functionally different responses, of fMRI. The scheme is based on super-resolution generative adversarial networks (SRGAN) that utilize a T2*-weighted image (T2*WI) dataset as a training reference. The efficacy of the scheme was evaluated through comparison with the activation maps obtained from the raw unpreprocessed functional data (raw fMRI). MRI images were acquired from 30 healthy volunteers using a 3 Tesla scanner. The modified SRGAN reconstructs a high-resolution image series from the original low-resolution fMRI data. For quantitative comparison, several metrics were calculated for both the STSS-SRfMRI and the raw fMRI activation maps. The ability to distinguish between two different finger-tapping tasks was significantly higher [p = 0.00466] for the reconstructed STSS-SRfMRI images than for the raw fMRI images. The results indicate that the functional resolution of the STSS-SRfMRI scheme is superior, which suggests that the scheme is a potential solution to realizing higher functional resolution in fMRI images obtained using 3T MRI.
書誌情報 Scientific Reports

巻 12, 号 10319, p. 1-9, 発行日 2022-06
出版者
出版者 Nature Publishing Group
ISSN
収録物識別子タイプ ISSN
収録物識別子 2045-2322
PubMed番号
識別子タイプ PMID
関連識別子 35725788
DOI
識別子タイプ DOI
関連識別子 10.1038/s41598-022-14421-5
関連サイト
識別子タイプ URI
関連識別子 https://www.nature.com/articles/s41598-022-14421-5
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