Noise reduction in direct multi-material decomposition for dual-energy CT

Abstract

Dual energy computed tomographic (DECT) enhances tissue characterization by obtaining two or three material images from two measurements at two different X-ray source potential. Recently, developing for multi-material decomposition (MMD) in DECT has been studied to obtain decomposed material images. MMD need to reduce noise and maintain spatial resolution of decomposed images. However, no studies have reported total nuclear variation (TVN) as noise suppression method for MMD to improve decomposition accuracy. We proposed a noise suppression using TVN for the direct MMD. The TVN method was applied to CT data before material decomposition to reduce noise. Tissue characterization Model 467 phantom was employed as the test object in this study. To investigate the effect of various basis materials, we selected four materials as basis materials. The volume fraction (VF) value was calculated to quantitatively evaluate quality of decomposed images. The results are compared to direct MMD method and proposed method. In all decomposed images, VF accuracies using proposed method were better than the direct MMD method. Also, proposed method can provide decomposed images with a small difference in separated density. In conclusion, proposed method could provide better quantitatively accurate images.