Sinogram restoration based on shape property in computed tomography

摘要: Abstract Low-dose computed tomography (CT) image sequences, obtained to reduce the risk of radiation exposure, can be seriously degraded by quantum noise and other kinds mechanical electrical effects. In order overcome this problem, we firstly present a sinogram restoration algorithm based on nonlinear optimization programs (NLP), including sequential quadratic programming (SQP) interior point method (IPM). Then, reconstructed is filtered back-projection (FBP) from smoothed projection data. A real-time scan was provided applying CUDA, which improves calculation speed precision. The effectiveness practicability proposed are validated utilizing digital phantom real clinical data experiments. advantage over techniques demonstrated means peak signal-noise ratio (PSNR) Euclidean distance original image. experimental results show that has excellent performance for low-dose CT imaging analysis.