Deep-learned time-signal intensity pattern analysis using an autoencoder captures magnetic resonance perfusion heterogeneity for brain tumor differentiation

Abstract Current image processing methods for dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) do not capture complex dynamic information of time-signal intensity curves. We investigated whether an autoencoder-based pattern analysis of DSC MRI captured representative temporal f...

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Autores principales: Ji Eun Park, Ho Sung Kim, Junkyu Lee, E.-Nae Cheong, Ilah Shin, Sung Soo Ahn, Woo Hyun Shim
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Acceso en línea:https://doaj.org/article/6aac4ed3f8ab4abebaa6c94e37576693
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