ABSTRACT
Concerns have been raised over x-ray radiation dose associated with repeated computed tomography (CT) scans for tumor surveillance and radiotherapy planning. In this paper, we present a low-dose CT image reconstruction method for improving low-dose CT image quality. The method proposed exploited rich redundancy information from previous normal-dose scan image for optimizing the non-local weights construction in the original non-local means (NLM)-based low-dose image reconstruction. The objective 3D low-dose volume and the previous 3D normal-dose volume were first registered to reduce the anatomic structural dissimilarity between the two datasets, and the optimized non-local weights were constructed based on the registered normal-dose volume. To increase the efficiency of this method, GPU was utilized to accelerate the implementation. The experimental results showed that this method obviously improved the image quality, as compared with the original NLM method, by suppressing the noise-induced artifacts and preserving the edge information.