Batch size: go big or go home? Counterintuitive improvement in medical autoencoders with smaller batch size.

Kerley, Cailey I; Cai, Leon Y; Tang, Yucheng; Beason-Held, Lori L; Resnick, Susan M; Cutting, Laurie E; Landman, Bennett A

Kerley, Cailey I; Cai, Leon Y; Tang, Yucheng; Beason-Held, Lori L; Resnick, Susan M; Cutting, Laurie E; Landman, Bennett A.

Afiliação

Kerley CI; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA.
Cai LY; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.
Tang Y; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA.
Beason-Held LL; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
Resnick SM; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
Cutting LE; Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN, USA.
Landman BA; Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA.

Proc SPIE Int Soc Opt Eng ; 124642023 Feb.

Article em En | MEDLINE | ID: mdl-37465095

Palavras-chave

autoencoder; batch size; brain MRI; electronic health record; latent space

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Observational_studies Idioma: En Revista: Proc SPIE Int Soc Opt Eng Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

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