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In this work we discuss a new algorithm for image reconstruction in half-scan fan-beam computed tomography (CT) and compare its performance with that of the conventional half-scan fan-beam filtered backprojection (FFBP) algorithm. Specifically, we investigate quality of reconstructed images when different weighting functions are used to normalize the half-scan data; we evaluate reconstructions from data that are acquired at different numbers of projection views; and we compare the noise properties of the new algorithm and the conventional half-scan FFBP algorithm. Numerical results in our studies suggest that the new algorithm is generally less susceptible to data noise and aliasing than is the half-scan FFBP algorithm. In particular, the new algorithm yields images with more uniform noise and resolution properties than does the FFBP algorithm. Such uniform properties can have potentially significant implication for estimation- and detection-tasks that are based upon CT images.