X-Ray CT using combined diagonally relaxed orthogonal projections (DROP) and quadratic regularization

Computed tomography (CT) aims to reconstruct an internal distribution of an object based on projection measurements. In the case of a limited number of projections, the reconstruction problem becomes very poorly posed. Practically, reconstruction algorithms play a crucial role in overcoming this problem. In this paper, DROP algorithm and quadratic regularization (orthogonal projections Relaxes diagonal) for image reconstruction, and in case of missing or incomplete data, in order to improve the reconstruction image quality. The numerical simulation results demonstrate that the suggested technique minimizes noise and artifacts while preserving structural information. The results are encouraging and indicate the effectiveness of the proposed method. A comparative study is done in order to examine the results with Kaczmarz method, will be implemented and applied to real images obtained by an X-ray tomography. To could verify the quality of image reconstruction we calculate SNR, MSE, PNSR.