Noise Suppression in Image-Domain Multi-Material Decomposition for Dual-Energy CT

Objective: Dual-energy CT (DECT) strengthens the material characterization and quantification due to its capability of material discrimination. The image-domain multi-material decomposition (MMD) via matrix inversion suffers from serious degradation of the signal-to-noise ratios (SNRs) of the decomposed images, and thus the clinical application of DECT is limited. In this paper, we propose a noise suppression algorithm based on the noise propagation for image-domain MMD. Methods: The noise in the decomposed images only distributes in two perpendicular directions and is suppressed by estimating the center of mass of the same-material pixel group vertically along the principal axis where the noise disturbance is minimal. The proposed method is evaluated using the line-pair and contrast-rod slices of the Catphan©600 phantom and one patient data set. We compared the proposed method with the direct inversion and the block-matching and three-dimensional (BM3D) filtration methods. Results: The results of Catphan©600 phantom and the patient show that the proposed method successfully suppresses the noise of the basis material images by one order of magnitude and preserves the spatial resolution of the decomposed images. Compared with the BM3D filtration method, the proposed method maintains the texture distribution of the decomposed images at the same SNR and the accuracy of the electron density measurement. Conclusion: The algorithm achieves effective noise suppression compared with the BM3D filtration while maintaining the spatial distribution of the decomposed material images. It is, thus, attractive for advanced clinical applications using DECT.