Adaptive Markovian model for 3D x-ray vascular reconstruction

Etienne P. Payot; Francoise J. Preteux; Regis Guillemaud; Yves L. Trousset

doi:10.1117/12.216355

11 August 1995 Adaptive Markovian model for 3D x-ray vascular reconstruction

Etienne P. Payot, Francoise J. Preteux, Regis Guillemaud, Yves L. Trousset

Proceedings Volume 2568, Neural, Morphological, and Stochastic Methods in Image and Signal Processing; (1995) https://doi.org/10.1117/12.216355
Event: SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, 1995, San Diego, CA, United States

Abstract

The Bayesian approach combined with the Markov random field approach provide a powerful and consistent mathematical framework for taking into account a priori knowledge and for regularizing ill-posed problems. Applied to 3D x-ray vascular reconstruction, such a combining approach requires a 3D object model describing the vascular tree. To take into account characteristic features of blood vessels, the proposed model performs a sort of shape analysis in order to estimate non-stationary parameters of the Markovian model. The global energy function is then expressed as a weighted combination of an adaptive smoothing potential which favors smoothing along the vessel direction; an enhancing potential which increases the contrast of small vessels; and a data-dependent term based on the difference between reprojection of the 3D reconstructed object and observed projections.

Citation Download Citation

Etienne P. Payot, Francoise J. Preteux, Regis Guillemaud, and Yves L. Trousset "Adaptive Markovian model for 3D x-ray vascular reconstruction", Proc. SPIE 2568, Neural, Morphological, and Stochastic Methods in Image and Signal Processing, (11 August 1995); https://doi.org/10.1117/12.216355

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