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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...
Autores principales: | Park, Ji Eun, Kim, Ho Sung, Lee, Junkyu, Cheong, E.-Nae, Shin, Ilah, Ahn, Sung Soo, Shim, Woo Hyun |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
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 |
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