Material decomposition with the multi-energy attenuation coefficient ratio by using a multiple discriminant analysis

The objective of this study was to develop a spectral CT system using a photon counting detector and to decompose materials by applying a multiple discriminant analysis (MDA) to the energy-dependent attenuation coefficient ratios. We imaged cylindrical phantoms of Polymethyl methacrylate (PMMA) with four holes filled with calcium chloride, iodine, and gold nanoparticle contrast agents. The attenuation coefficients were measured via reconstructed multi-energy images, and the linear attenuation ratio was used for material identification. The MDA projection matrix, determined from training phantoms, was used to identify the four materials in the testing phantoms. For quantification purposes, the relationships between the attenuation coefficients at multiple energy bins and the concentrations were characterized by using the least-squares method for each material. The mean identification accuracy for each of the three materials were 0.94 ± 0.09 for iodine, 0.96 ± 0.07 for gold nanoparticles, and 0.92 ± 0.05 for calcium chloride. The mean quantification errors were 1.90 ± 1.58% for iodine, 3.85 ± 3.13% for gold nanoparticle, and 3.40 ± 2.62% for calcium chloride. The developed multi-energy CT system based on the photon-counting detector with MDA can precisely decompose the four materials.