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We investigate performance tradeoffs for a class of filtered backprojection (FBP) image reconstruction algorithms. The recently developed fast hierarchical backprojection asymptotically achieves the same O(N2 log N) cost as Fourier-based methods while retaining many advantages of the FBP technique. In this paper, we provide a detailed cost and performance analysis of the algorithm on a general purpose platform. Based on carefully tuned implementations of both the direct and the hierarchical backprojection, we explore the tradeoffs between distortion and runtime by varying several algorithm and implementation choices. Experimental results show that, given the desired performance, the choice of algorithm parameters is not obvious and largely depends on the image properties and the underlying computer platform.