A flexible iterative method for 3D reconstruction from X-ray projections

Laurent Launay and Pierre Bouchet and Eric Maurincomme and Marie-Odile Berger and Jean-Laurent Mallet. ( 1996 )
in: 13th gOcad Meeting, ASGA

Abstract

The problem of reconstructing a three-dimensional image of an object from a few number of X-ray projections is highly underdetermincd. We propose a flexible method based on the regularization of the inverse linear problem with a generai quadratic criterion. The minimization is performed by an iterative algoritm with a Gauss-Seidel behaviour. Thanks to the Discrete Smooth Interpolation (DSl) formulation, additional linear constraints are inserted, and the method is ensured to converge to the unique minimum. The application of this method is shown for 3D reconstruction of cerebral blood vessels from six projections, and the effect of various criteria is compared to the result of other algebraic methods.

Download / Links

    BibTeX Reference

    @inproceedings{LaunayRM1996a,
     abstract = { The problem of reconstructing a three-dimensional image of an object from a few number of X-ray projections is highly underdetermincd. We propose a flexible method based on the regularization of the inverse linear problem with a generai quadratic criterion. The minimization is performed by an iterative algoritm with a Gauss-Seidel behaviour. Thanks to the Discrete Smooth Interpolation (DSl) formulation, additional linear constraints are inserted, and the method is ensured to converge to the unique minimum. The application of this method is shown for 3D reconstruction of cerebral blood vessels from six projections, and the effect of various criteria is compared to the result of other algebraic methods. },
     author = { Launay, Laurent AND Bouchet, Pierre AND Maurincomme, Eric AND Berger, Marie-Odile AND Mallet, Jean-Laurent },
     booktitle = { 13th gOcad Meeting },
     month = { "june" },
     publisher = { ASGA },
     title = { A flexible iterative method for 3D reconstruction from X-ray projections },
     year = { 1996 }
    }