Iterative X-ray cone-beam tomography for metal artifact reduction and local region reconstruction

X-ray cone-beam reconstruction from incomplete projection data has importan t practical applications, especially in microtomography. We developed expec tation maximization (EM)-type and algebraic reconstruction technique (ART)- type iterative cone-beam reconstruction algorithms for metal artifact reduc tion and local reconstruction from truncated data. These iterative algorith ms are adapted from the emission computerized tomography (CT) EM formula an d the ART. A key step in our iterative algorithms is introduction of a proj ection mask and computation of a 3-D spatially varying relaxation factor th at allows compensation for beam divergence and data incompleteness. The alg orithms are simulated with projection data synthesized from mathematical ph antoms. In simulation, the EM-type and ART-type iterative algorithms are de monstrated to be effective for metal artifact reduction and local region re construction. They perform similarly in terms of visual quality, image nois e, and discrepancy between measured and reprojected data. The EM-type and A RT-type iterative cone-beam reconstruction algorithms have potential for me tal artifact reduction and local region reconstruction in X-ray CT.