Selective Projection-rebin FDK Algorithm and its Efficient GPU Implementation

FDK algorithm is widely used in computed tomography. However, the traditional rebin FDK algorithm heavily consumes memories, thus the reconstruction efficiency is low. Aiming to solve the problem, a selective projection-rebin FDK algorithm is proposed in this paper. By analyzing the geometrical relationship between the original projections and rebined ones, the least amount of cone-beam projections during each round of data rearrangement is derived. Circular queue is used to selectively load certain frames of cone-beam projections, which substantially reduces the memory-consumption. Based on graphic processing unit, the new algorithm is optimized for its parallelism performance, and the speed of the parallel method is boosted significantly. Experiments for the reconstruction of 512³ are performed to verify the effectiveness of the algorithm. Without loss of reconstruction accuracy, its memory consumption is reduced to 1/3 and 1/5 of the traditional for simulation data and real data respectively. The new algorithm, reducing the memory-consumption substantially, is the development of traditional rebin FDK algorithm, and it solves the problem of reconstruction for mass projections.