Material Classification Based on Dual-Energy Micro-Ct Images by the Gaussian Mixture Model.

Material Classification Based on Dual-Energy Micro-Ct Images by the Gaussian Mixture Model. Publisher

Mamizadeh H^{1, 2} ; Solgi R¹ ; Carrier JF^{3, 4} ; Ghadiri H^{1, 2}

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1. Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran
2. Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Equipment Institute, University of Medical Sciences, Tehran, Iran
3. Physics Department, Universite de Montreal, Montreal, QC, Canada
4. Research Center, Centre Hospitalier de l'Universite de Montreal (CRCHUM), Montreal, QC, Canada

Source: Journal of Instrumentation Published:2022

Abstract

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 parameters and performs classification based on the posterior probability with a pre-determined cluster number. Our studies on dual-energy images of a phantom showed that the distribution of linear attenuation coefficient of different materials on the scatter diagram has a Gaussian distribution, and clusters can be classified using model-based clustering. The result of this classification method is related to the actual materials in the phantom, where a specific cluster represents each material. This classification method can be potentially used when the clusters are overlapped and the material is separated with high accuracy. © 2022 IOP Publishing Ltd and Sissa Medialab.

Style	Citing Format
MLA	Mamizadeh H, et al.. "Material Classification Based on Dual-Energy Micro-Ct Images by the Gaussian Mixture Model.." Journal of Instrumentation, vol. 17, no. 2, 2022, pp. -.
APA	Mamizadeh H, Solgi R, Carrier JF, Ghadiri H (2022). Material Classification Based on Dual-Energy Micro-Ct Images by the Gaussian Mixture Model.. Journal of Instrumentation, 17(2), -.
Chicago	Mamizadeh H, Solgi R, Carrier JF, Ghadiri H. "Material Classification Based on Dual-Energy Micro-Ct Images by the Gaussian Mixture Model.." Journal of Instrumentation 17, no. 2 (2022): -.
Harvard	Mamizadeh H et al. (2022) 'Material Classification Based on Dual-Energy Micro-Ct Images by the Gaussian Mixture Model.', Journal of Instrumentation, 17(2), pp. -.
Vancouver	Mamizadeh H, Solgi R, Carrier JF, Ghadiri H. Material Classification Based on Dual-Energy Micro-Ct Images by the Gaussian Mixture Model.. Journal of Instrumentation. 2022;17(2):-.
BibTex	@article{ author = {Mamizadeh H and Solgi R and Carrier JF and Ghadiri H}, title = {Material Classification Based on Dual-Energy Micro-Ct Images by the Gaussian Mixture Model.}, journal = {Journal of Instrumentation}, volume = {17}, number = {2}, pages = {-}, year = {2022} }
RIS	TY - JOUR AU - Mamizadeh H AU - Solgi R AU - Carrier JF AU - Ghadiri H TI - Material Classification Based on Dual-Energy Micro-Ct Images by the Gaussian Mixture Model. JO - Journal of Instrumentation VL - 17 IS - 2 SP - EP - PY - 2022 ER -

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