A new voxellation scheme for iterative CBCT reconstruction with less computational cost: Polar voxel design of an isosceles-triangle shape

Abstract

We propose a new voxellation scheme for iterative cone-beam computed tomography (CBCT) reconstruction with less computational cost. Here, the voxel configuration is designed with an isosceles-triangle shape by using polar coordinates, exploiting the rotational symmetries inherent to the CBCT acquisition geometry and keeping the uniformity of the voxel size as well. By using polar symmetries, we can reduce the size of the system matrix by a factor corresponding to the number of acquired projections, which speeds up the construction of the system matrix and, thus, allows iterative methods to be applied to practical applications within a reasonable reconstruction time. In this study, we implemented an efficient algorithm to reconstruct the system matrix based upon the proposed voxellation scheme and incorporated it into a built-in iterative CBCT reconstruction algorithm based the gradient-projection Barzilai-Borwein (GPBB) method, and we performed systematic simulation works to investigate the imaging characteristics. Our results indicate that the voxellation scheme we proposed in study seems to be effective in reducing the computational time and the memory burden considerably.