Performance Evaluation of Material Decomposition for the Dual-Energy CT Images Reconstructed by MAP-EM Algorithm

Dual energy computed tomography (DECT) plays a significant role in medical application and public security. The accuracy of the decomposition relies much on the quality of the reconstructed images. Images reconstructed by traditional methods generally suffer from significant noise, leading to the low accuracy of the material decomposition and identification. In order to solve the above problem, the maximum a posteriori expectation maximization (MAP-EM) is employed to reconstruct the CT images for the material decomposition, and the performance of the material decomposition is evaluated. A dual source DECT system with 140/80 kVp are simulated by Geant4. The MAP-EM algorithm is used to reconstruct the images from the collected projection at two different tube voltages. And then the basis material decomposition coefficient images are obtained with the basis material decomposition coefficient equations. Comparing with the commonly used filtered back projection (FBP) algorithm, the MAP-EM algorithm reduced noise in polyethylene region on the reconstructed images at two tube voltages with 80 kVp and 140 kVp up to 33.23%, 26.43% respectively. The contrast-to-noise ratios (CNRs) of the aluminum images were improved by 54.13% and 41.02%, that of the HA images by 52.75% and 40.47%, and that of the salt water images by 52.84% and 40.22% at the above two tube voltages. Compared with DE-FBP, the decomposition error of DE-MAP was reduced by 95.94% to 99.09%. In conclusion, the result shows superior performance on material decomposition and identification with high CNRs and low decomposition errors with the DECT images reconstructed by MAP-EM algorithm.