In many applications of computed tomography, we cannot acquire the projection data at all angles evenly spaced over 360°. In such cases, the computed tomography images reconstructed using a limited number of projections, measured over a narrow angle range, are characterized by approximately elliptical distortion along the view angles used and poor contrast at angles not used (anisotropic resolution). This systematic geometric distortion is caused by the 2-D point spread function of the reconstruction process. In this paper, we show that such geometric distortion and other artifacts introduced in the reconstruction process can be reduced substantially by deconvolution performed via Wiener filtering using a priori knowledge derived from the given projections. The 2-D system transfer function used in the deconvolution is obtained from the reconstruction of a test image by the same reconstruction algorithm which has been used for reconstructing the unknown object.
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