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arXiv · 1208.2070

Microstructure identification via detrended fluctuation analysis of ultrasound signals

Paulo G. Normando·Romao S. Nascimento·Elineudo P. Moura·Andre P. Vieira
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Abstract

We describe an algorithm for simulating ultrasound propagation in random one-dimensional media, mimicking different microstructures by choosing physical properties such as domain sizes and mass densities from probability distributions. By combining a detrended fluctuation analysis (DFA) of the simulated ultrasound signals with tools from the pattern-recognition literature, we build a Gaussian classifier which is able to associate each ultrasound signal with its corresponding microstructure with a very high success rate. Furthermore, we also show that DFA data can be used to train a multilayer perceptron which estimates numerical values of physical properties associated with distinct microstructures.

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BibTeXRIS

Paulo G. Normando, Romao S. Nascimento, Elineudo P. Moura, Andre P. Vieira. 2012-12-21. Microstructure identification via detrended fluctuation analysis of ultrasound signals. https://doi.org/10.1103/physreve.87.043304

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