A Bayesian Approach to Shape Reconstruction of a Compact Object from a Few Number of Projections

Details A Bayesian Approach to Shape Reconstruction of a Compact Object from a Few Number of Projections A Bayesian Approach to Shape Reconstruction of a Compact Object from a Few Number of Projections

2001-11-14

arxiv.org/abs/physics/0111120v1

Physics

Data Analysis, Statistics and Probability

Presented at MaxEnt96. Appeared in Proceedings of the Maximum Entropy Conference, Berg-en-Dal, South Africa, M. Sears, V. Nede

Scientific paper

Image reconstruction in X ray tomography consists in determining an object from its projections. In many applications such as non destructive testing, we look for an image who has a constant value inside a region (default) and another constant value outside that region (homogeneous region surrounding the default). The image reconstruction problem becomes then the determination of the shape of that region. In this work we model the object (the default region) as a polygonal disc and propose a new method for the estimation of the coordinates of its vertices directly from a very limited number of its projections. Keywords: Computed Imaging, Tomography, Shape reconstruction, Non destructive testing, Regularization, Bayesian estimation, Deformable contours.

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