A Bayesian Approach to Shape Reconstruction of a Compact Object from a Few Number of Projections
Abstract
Description
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.
Presented at MaxEnt96. Appeared in Proceedings of the Maximum Entropy Conference, Berg-en-Dal, South Africa, M. Sears, V. Nedeljkovic, N.E. Pendock and S. Sibisi (Ed.), pp 68-77
Presented at MaxEnt96. Appeared in Proceedings of the Maximum Entropy Conference, Berg-en-Dal, South Africa, M. Sears, V. Nedeljkovic, N.E. Pendock and S. Sibisi (Ed.), pp 68-77