Adaptive combined denoising based low-dose X-ray CT reconstruction

X-ray Computed Tomography (CT) has been widely applied in clinical domain, especially in the field of diagnosis and treatment. X-rays is harmful to human health. Minimizing radiation dose as more as possible has been a significant concern in CT imaging filed. One way to reduce the radiation dose in the data acquisition process is to reduce the current of the x-ray source. However this will degrade the quality of the reconstructed image with strong noise. In this paper, we propose an adaptive combined denoising method for restoration of low-dose CT projection data (i.e., sinogram). The method unites LAWML and WienerChop in the wavelet domain. Simulated experimental results demonstrate that the proposed method performs better than conventional filters, such as the Hanning filter, in lowering the noise and preserving the image resolutions.