Gain of KL-domain adaptive FBP image reconstruction for 4-D dynamic CT

Four-dimensional dynamic computed tomography (4D-dCT) plays an important role in radiation treatment planning, delivery, and verification for lung cancer management, in addition to heart studies. 4D-dCT acquires multiple repeated measurements from the same patient. Therefore, the radiation dose during a 4D-dCT procedure is much higher than a routine 3D CT study. Low-dose scans for 4D-dCT is needed. In this work, a new reconstruction strategy is proposed to address the noise problem associated with low-dose dynamic CT scans. It first applies the Karhunen-Loeve (KL) transform to the neighboring phases of 4D-dCT noise sinogram to consider the data correlation along the time dimension. In the KL domain, the independent 3D principal components are arranged according to their signal-to-noise ratios (which are reflected by their eigenvalues). It then adapts the filtered backprojection (FBP) algorithm to reconstruct each principal component in the KL domain, where the filter´s cutoff frequency is adaptive to the eigenvalue of the corresponding KL component. Finally, the 4D- dCT image is obtained by inverse KL transform. A patient study was performed to demonstrate the effectiveness of the proposed strategy with comparison to a direct FBP reconstruction which does not consider the correlation or employ the KL transform. The gain of the KL-domain adaptive FBP reconstruction was measured quantitatively by noise-resolution tradeoff study.