Deep Learning-Driven Transformation: A Novel Approach for Mitigating Batch Effects in Diffusion MRI Beyond Traditional Harmonization.

Wada, Akihiko; Akashi, Toshiaki; Hagiwara, Akifumi; Nishizawa, Mitsuo; Shimoji, Keigo; Kikuta, Junko; Maekawa, Tomoko; Sano, Katsuhiro; Kamagata, Koji; Nakanishi, Atsushi; Aoki, Shigeki

Wada, Akihiko; Akashi, Toshiaki; Hagiwara, Akifumi; Nishizawa, Mitsuo; Shimoji, Keigo; Kikuta, Junko; Maekawa, Tomoko; Sano, Katsuhiro; Kamagata, Koji; Nakanishi, Atsushi; Aoki, Shigeki.

Afiliación

Wada A; Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.
Akashi T; Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.
Hagiwara A; Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.
Nishizawa M; Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.
Shimoji K; Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.
Kikuta J; Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.
Maekawa T; Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.
Sano K; Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.
Kamagata K; Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.
Nakanishi A; Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.
Aoki S; Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.

J Magn Reson Imaging ; 2023 Oct 25.

Article en En | MEDLINE | ID: mdl-37877463

Palabras clave

batch effect mitigation; deep learning; diffusion MRI; image diversity

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: J Magn Reson Imaging Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2023 Tipo del documento: Article País de afiliación: Japón

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