A comparison of rotation-based methods for iterative reconstruction algorithms

Rotation-based projectors and backprojectors offer unique trade-offs between accuracy, computational complexity, and smoothing. The authors analyzed six different rotation methods for generating projections and iterative reconstructions of tomographic data. Nearest neighbor, upsampled nearest neighbor, bilinear interpolation, and bicubic interpolation were all used to determine the values at rotated grid points. A decomposition of the rotation transformation matrix into three components was also investigated. Linear and cubic interpolation were used in the three-pass method. For all of the methods, mean normalized square errors were computed. The authors´ results demonstrate the tradeoffs associated with the different methods and suggest that the three-pass method with cubic interpolation offers a computationally efficient approach with accuracy between that of bilinear and bicubic interpolation