Reconstruction of vascular networks using three-dimensional models

IEEE Transactions on Medical Imaging
P HallP Andreae

Abstract

Reconstructing vasculature in three dimensions is a challenging problem. Early approaches concentrated on coronary vasculature in X-ray images, recent work uses magnetic resonance imagery of cerebral vasculature. In both cases a priori information has been used, and often the way this is represented has proven limiting to the scope of applications supported. For example, a particular representation may be useful only for X-ray images. This paper addresses two issues: 1) representing a collection of vasculature and 2) the reconstruction of individual vasculature from images. Our representation learns the variations in branching structures and vessel shapes that occur between individuals. It supports a vascular catalogue containing three-dimensional (3-D) anatomical models. The representation is task independent; here we use it to reconstruct vasculature from images. Our algorithm has four features to which we draw attention: 1) it is not premised wholly upon X-ray images (though that is our focus here); 2) it produces several feasible solutions rather than one; 3) it can generalize from the catalogue to reconstruct instances not yet learned; 4) it exhibits polynomial time complexity, reasonable memory consumption, and is reliabl...Continue Reading

References

Feb 1, 1997·IEEE Transactions on Medical Imaging·M SonkaS M Collins
Jan 1, 1996·IEEE Transactions on Medical Imaging·R Kutka, S Stier
Jan 1, 1996·IEEE Transactions on Medical Imaging·W E HigginsE L Ritman
Jan 1, 1994·IEEE Transactions on Medical Imaging·T V Nguyen, J Sklansky
Jan 1, 1991·IEEE Transactions on Medical Imaging·J A Fessler, A Macovski

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Citations

Oct 8, 1999·IEEE Transactions on Bio-medical Engineering·A WahleM Sonka
Jan 11, 2000·IEEE Transactions on Medical Imaging·K HarisG Louridas
Jun 30, 2000·IEEE Transactions on Medical Imaging·A HooverM Goldbaum
Sep 3, 2010·Biofabrication·William Lafayette MondyLes A Piegl

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