This master’s thesis will develop a novel approach using diffusion models for 3D CT reconstruction. The process will begin with denoising a highly blurred and noisy initial reconstruction from FBP or SIRT, aiming to enhance the quality of reconstructions obtained from a limited number of projection data on arbitrary trajectories. This research will focus on optimizing the denoising process to improve the output, advancing CT imaging capabilities with limited input data.