Iterative closest curve: A framework for curvilinear structure registration application to 2D/3D coronary arteries registration

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Abstract

Treatment coronary arteries endovascular involves catheter navigation through patient vasculature. The projective angiography guidance is limited in the case of chronic total occlusion where occluded vessel can not be seen. Integrating standard preoperative CT angiography information with live fluoroscopic images addresses this limitation but requires alignment of both modalities. This article proposes a structure-based registration method that intrinsically preserves both the geometrical and topological coherencies of the vascular centrelines to be registered, by the means of a dedicated curve-to-curve distance pairs of closest curves are identified, while pairing their points. Preliminary experiments demonstrate that the proposed approach performs better than the standard Iterative Closest Point method giving a wider attraction basin and improved accuracy. © 2013 Springer-Verlag.

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Benseghir, T., Malandain, G., & Vaillant, R. (2013). Iterative closest curve: A framework for curvilinear structure registration application to 2D/3D coronary arteries registration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8149 LNCS, pp. 179–186). https://doi.org/10.1007/978-3-642-40811-3_23

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