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Proceedings Paper

Curve-based 2D-3D registration of coronary vessels for image guided procedure
Author(s): Luc Duong; Rui Liao; Hari Sundar; Benoit Tailhades; Andreas Meyer; Chenyang Xu
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Paper Abstract

3D roadmap provided by pre-operative volumetric data that is aligned with fluoroscopy helps visualization and navigation in Interventional Cardiology (IC), especially when contrast agent-injection used to highlight coronary vessels cannot be systematically used during the whole procedure, or when there is low visibility in fluoroscopy for partially or totally occluded vessels. The main contribution of this work is to register pre-operative volumetric data with intraoperative fluoroscopy for specific vessel(s) occurring during the procedure, even without contrast agent injection, to provide a useful 3D roadmap. In addition, this study incorporates automatic ECG gating for cardiac motion. Respiratory motion is identified by rigid body registration of the vessels. The coronary vessels are first segmented from a multislice computed tomography (MSCT) volume and correspondent vessel segments are identified on a single gated 2D fluoroscopic frame. Registration can be explicitly constrained using one or multiple branches of a contrast-enhanced vessel tree or the outline of guide wire used to navigate during the procedure. Finally, the alignment problem is solved by Iterative Closest Point (ICP) algorithm. To be computationally efficient, a distance transform is computed from the 2D identification of each vessel such that distance is zero on the centerline of the vessel and increases away from the centerline. Quantitative results were obtained by comparing the registration of random poses and a ground truth alignment for 5 datasets. We conclude that the proposed method is promising for accurate 2D-3D registration, even for difficult cases of occluded vessel without injection of contrast agent.

Paper Details

Date Published: 13 March 2009
PDF: 10 pages
Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 72610S (13 March 2009); doi: 10.1117/12.811874
Show Author Affiliations
Luc Duong, Siemens Corporate Research (United States)
Rui Liao, Siemens Corporate Research (United States)
Hari Sundar, Siemens Corporate Research (United States)
Benoit Tailhades, Siemens Corporate Research (United States)
Andreas Meyer, Siemens AG (Germany)
Chenyang Xu, Siemens Corporate Research (United States)


Published in SPIE Proceedings Vol. 7261:
Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling
Michael I. Miga; Kenneth H. Wong, Editor(s)

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