Multi-Parametric Ultrasound Tissue Characterization (Mutc) As A Surrogate To Magnetic Resonance Imaging (Mri) For Non-Alcoholic Fatty Liver Disease (Nafld) Characterization.

PROCEEDINGS OF THE 2020 IEEE INTERNATIONAL ULTRASONICS SYMPOSIUM (IUS)(2020)

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摘要
Ultrasound tissue characterization (UTC) provides ultrasound elastography and quantitative metrics extracted from RF data for evaluating tissue mechanics and microstructure. Our goal is to learn multi-parametric models on the same patient population for regression of Magnetic Resonance Imaging Proton-Density Fat-Fraction (MRI-PDFF). The results show that non-linear multi-parameteric UTC models (e.g., multi-layer perceptron, random forests, Gaussian processes) are superior to multi-linear regression approaches and outperform qualitative radiologist assessment. Integration of radiologist feedback with UTC further improves PDFF regression.
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关键词
non-alcoholic fatty liver disease, elastography, attenuation, speckle statistics, spectroscopy, machine learning, multi-parametric regression
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