Material decomposition for spectral X-ray CT: application to calcium and iodine identification

Spectral X-ray CT is able to discriminate transmitted photons corresponding to different energy bins and produce spectral information with one data acquisition, making it possible to separate various materials. We propose a material decomposition method for spectral X-ray CT based on least log- squares criterion for the objective function, to identify calcium and iodine. We also simulated the noisy spectral X-ray CT imaging of a computational human thorax phantom. Extra calcium and iodine solutions at various concentrations (calcium: 30, 50, 100, 150, 200mg/cc; iodine: 5, 15, 25, 35, 45mg/cc) were placed within the heart region of the phantom. Decomposition results of the proposed method show that calcium and iodine are well separated and quantified from soft tissues, with 23.06%-4.98% average relative errors at different concentrations for calcium and 22.59%-5.69% for iodine.