Fast Implementation of Algebraic Methods for 3D Reconstruction from Cone-Beam Data

The prime motivation of this work is to devise techniques that make the algebraic reconstruction technique (ART) and related methods more efficient for routine clinical use, while not compromising their accuracy. Since most of the computational effort of ART is spent for projection/backprojection operations, the authors first seek to optimize the projection algorithm. Existing projection algorithms are surveyed and it is found that these algorithms either lack accuracy or speed, or are not suitable for cone-beam reconstruction. The authors hence devise a new and more accurate extension to the splatting algorithm, a well-known voxel-driven projection method. They also describe a new three-dimensional (3-D) ray-driven projector that is considerably faster than the voxel-driven projector and, at the same time, more accurate and perfectly suited for the demands of cone beam. The authors then devise caching schemes for both ART and simultaneous ART (SART), which minimize the number of redundant computations for projection and backprojection and, at the same time, are very memory conscious. They find that with caching, the cost for an ART projection/backprojection operation can be reduced to the equivalent cost of 1.12 projections. They also find that SART, due to its image-based volume correction scheme, is considerably harder to accelerate with caching. Implementations of the algorithms yield runtime ratios T/sub SART//T/sub ART/ between 1.5 and 1.15, depending on the amount of caching used.