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Comparison of handcrafted features and convolutional neural networks for liver MR image adequacy assessment

We propose a random forest classifier for identifying adequacy of liver MR images using handcrafted (HC) features and deep convolutional neural networks (CNNs), and analyze the relative role of these two components in relation to the training sample size. The HC features, specifically developed for...

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Detalles Bibliográficos
Autores principales: Lin, Wenyi, Hasenstab, Kyle, Moura Cunha, Guilherme, Schwartzman, Armin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7683555/
https://www.ncbi.nlm.nih.gov/pubmed/33230152
http://dx.doi.org/10.1038/s41598-020-77264-y