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

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 features t...

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Detalles Bibliográficos
Autores principales: Park, Ji Eun, Kim, Ho Sung, Lee, Junkyu, Cheong, E.-Nae, Shin, Ilah, Ahn, Sung Soo, Shim, Woo Hyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7723041/
https://www.ncbi.nlm.nih.gov/pubmed/33293590
http://dx.doi.org/10.1038/s41598-020-78485-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7723041/
https://www.ncbi.nlm.nih.gov/pubmed/33293590
http://dx.doi.org/10.1038/s41598-020-78485-x

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