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

Abstract 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 devel...

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Autores principales: Wenyi Lin, Kyle Hasenstab, Guilherme Moura Cunha, Armin Schwartzman
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Acceso en línea:https://doaj.org/article/8163ba569a264ccba16c94fb8f0d2882
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