Reconstruction of smooth distributions from a limited number of projections.
Two reconstruction methods that recognize smoothness to be a priori information and use numerically spacelimited basis functions have been developed. The first method is a modification of the well-known convolution method and uses such basis functions for the projections. The second method is a continuous algebraic reconstruction technique that employs consistent basis functions for the projections as well as the distribution and makes use of other a priori information like the constraints on the domain as well as the range of the distribution in a rigorous way. The efficacy of these methods has been demonstrated using a limited number of projections synthetically generated from a distribution phantom.
Ravichandran
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Gouldin
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