Noise reduction for helical computed tomography using coupled projections

Helical computed tomography (HCT) has demonstrated the effectiveness in virtual colonoscopy (VC) or CTcolonography (CTC). One major concern with this clinical application is associated with the risk of high radiation exposure, especially for its use for screening purpose at a large population. In this work, we presented an improved Karhunen-Loeve (KL) domain penalized weighted least-squares (PWLS) strategy which considers the data correlations among the projection rays mainly due to partially overlap while system rotates. Two 1-dimensional (1D) projections, which called coupled projections (CPs), are composed according to the geometry. Each element of the 1D projection is carefully selected for a specific point within 2π angle along the system rotates and thus a highly correlation can be observed between any specific projection and the CPs. These highly correlated projections can be treated by an adaptive KL-PWLS strategy for accurate noise reduction. This method has been implemented and tested on computer simulated sinograms which mimic low-dose CT scans. The reconstructed images by the presented strategy demonstrated the potential of ultra low-dose CT application.