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.
Diffusion Model-Based 3D CT Reconstruction for Arbitrary Trajectories
Type: MA thesis
Status: running
Date: March 1, 2025 - September 30, 2025
Supervisors: Linda-Sophie Schneider, Chengze Ye, Andreas Maier