Abstract

In this work, we introduced an algorithm for image reconstruction in helical cone-beam CT based upon the backprojection-filtration (BPF) algorithm. This algorithm is a backprojection-filtration-type algorithm that reconstructs images from rebinned data. It retains the properties of the original BPF algorithm in that it requires minimum data and can reconstruct ROI images from truncated data. More importantly, due to the elimination of the spatially-variant weighting factor in the backprojection, it may improve the noise properties in reconstructed images. We have performed computer-simulation studies to investigate the ROI-image reconstruction and noise properties of this algorithm, and the quantitative results verify and demonstrate the proposed algorithm.

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