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Proceedings Paper

Wiener Filtering For Deconvolution Of Geometric Artifacts In Limited-View Image Reconstruction
Author(s): Atam P. Dhawan; Rangaraj M. Rangayyan; R. Gordon
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Paper Abstract

Computed Tomography (CT) 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. This systematic geometric distortion is caused by the two dimensional 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 two-dimensional system transfer function used in the deconvolution is obtained from the reconstruction of a test image by a linear reconstruction algorithm (unconstrained multiplicative Algebraic Reconstuction Technique).

Paper Details

Date Published: 3 August 1984
PDF: 5 pages
Proc. SPIE 0515, Medical Images and Icons, (3 August 1984); doi: 10.1117/12.964749
Show Author Affiliations
Atam P. Dhawan, University of Manitoba (Canada)
Rangaraj M. Rangayyan, University of Manitoba (Canada)
R. Gordon, University of Manitoba (Canada)

Published in SPIE Proceedings Vol. 0515:
Medical Images and Icons
Andre J. Duerinckx; Murray H. Loew; Judith M. S. Prewitt, Editor(s)

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