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Proceedings Paper

Statistical Refinement Of Transmission Computed Tomograms In High Photon Counting Noise
Author(s): Ken Sauer; Bede Liu
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Paper Abstract

Tomographic reconstruction is conventionally performed by algorithms derived from deterministic views of the Radon transform inversion problem. Probably the two best-known approaches are convolution backprojection (CBP), and the algebraic reconstruction technique (ART). ART treats the image pixel values as unknowns in a very large set of linear equationsl. The iterative steps in ART can be thought of as a succession of projections onto convex sets, each of which includes all images satisfying one of the observed projection values. Standard ART includes no noise compensation, while the more widely commercially used CBP includes compensation for photon counting noise in projection data, but implicitly assumes stationarity. In many common imaging problems, the results of this assumption are not serious, since the object may be relatively homogeneous, or corruption in the image may be dominated by effects not directly associated with photon counting noise. But reconstructions of nonhomogeneous objects from low dosage transmission data may involve nonstationary, nonisotropic noise patterns which result from the data dependence of noise statistics in projections.

Paper Details

Date Published: 1 November 1989
PDF: 8 pages
Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); doi: 10.1117/12.970104
Show Author Affiliations
Ken Sauer, Princeton University (United States)
Bede Liu, Princeton University (United States)

Published in SPIE Proceedings Vol. 1199:
Visual Communications and Image Processing IV
William A. Pearlman, Editor(s)

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