Abstract

Cone-beam computed tomography (CT) is an emerging imaging technology, as it provides all projections needed for three-dimensional (3D) reconstruction in a single spin of the Xray source-detector pair. This facilitates fast, low-dose data acquisition as required for imaging fast moving objects, such as the heart, and intra-operative CT applications. Current cone-beam reconstruction algorithms mainly employ the Filtered-Backprojection (FBP) approach. In this dissertation, a different class of reconstruction algorithms is studied: the algebraic reconstruction methods. Algebraic reconstruction starts from an initial guess for the reconstructed object and then performs a sequence of iterative grid projections and correction backprojections until the reconstruction has converged. Algebraic methods have many advantages over FBP, such as better noise tolerance and better handling of sparse and non-uniformly distributed projection datasets. So far, the main repellant for using algebraic methods...

Citations