Image Fusion for Low-Dose Computed Tomography Reconstruction

Reducing radiation dose as more as possible has been a significant concern in CT imaging field. Although lower the X-ray tube current (mAs) is an easy way to reduce the radiation dose directly, the associated reconstructed image quality will degrade significantly due to the excessive noise in projection data. For high quality low-dose CT reconstrnction, the projection data restoration methods can adaptively suppress the noise in the highest attenuation regions. However, these methods remove not only the noise but also some edge information, which result in the reconstructed image suffers noticeable resolutions loss. In addition, it is known that a high-performance filtering methods for low-dose CT image restoration can achieve noticeable noise suppression without a significant resolution loss, but the noise-induced artifacts cannot be removed effectively due to the complex artifacts characteristics in low-dose CT image. Based on above observations, in this paper, we propose an image fusion method for low-dose CT reconstruction by making full use of the advantages of both the low-dose CT sinogram data restoration and image domain advanced edge-preserving filtering. Simulated and clinical experimental results demonstrate the presented method performs better than the existing methods in lowering the noise and preserving the image edge, without noticeable sacrifice of the spatial resolution.