Material classification based on Dual-Energy Micro-CT images by the Gaussian mixture model

This study aimed to implement an unsupervised classification method through the Gaussian mixture model to classify different materials using the scatter diagram of the linear attenuation coefficients acquired from dual-energy micro-CT imaging. This method estimates each cluster's distribution p...

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Veröffentlicht in:	Journal of instrumentation 2022-02, Vol.17 (2), p.P02001
Hauptverfasser:	Mami-Zadeh, H., Solgi, R., Carrier, J.-F., Ghadiri, H.
Format:	Artikel
Sprache:	eng
Schlagworte:	Attenuation coefficients Classification Clustering Computed tomography Conditional probability Image acquisition Image classification Normal distribution Probabilistic models Scattering Statistical analysis
Online-Zugang:	Volltext
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