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Proceedings Paper

Adaptive Markovian model for 3D x-ray vascular reconstruction
Author(s): Etienne P. Payot; Francoise J. Preteux; Regis Guillemaud; Yves L. Trousset
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Paper 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.

Paper Details

Date Published: 11 August 1995
PDF: 12 pages
Proc. SPIE 2568, Neural, Morphological, and Stochastic Methods in Image and Signal Processing, (11 August 1995); doi: 10.1117/12.216355
Show Author Affiliations
Etienne P. Payot, Institut National des Telecommunications, LETI/Commisariat a l'Energie Atomique, GE Medica (France)
Francoise J. Preteux, Institut National des Telecommunications (France)
Regis Guillemaud, LETI/Commisariat a l'Energie Atomique (France)
Yves L. Trousset, General Electric Medical Systems (France)

Published in SPIE Proceedings Vol. 2568:
Neural, Morphological, and Stochastic Methods in Image and Signal Processing
Edward R. Dougherty; Francoise J. Preteux; Sylvia S. Shen, Editor(s)

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