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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...
| Autores principales: | , , , |
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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/PMC7683555/ https://www.ncbi.nlm.nih.gov/pubmed/33230152 http://dx.doi.org/10.1038/s41598-020-77264-y |