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Proceedings Paper

Significant acceleration of 2D-3D registration-based fusion of ultrasound and x-ray images by mesh-based DRR rendering
Author(s): Markus Kaiser; Matthias John; Anja Borsdorf; Peter Mountney; Razvan Ionasec; Alois Nöttling; Philipp Kiefer; Jörg Seeburger; Thomas Neumuth
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Paper Abstract

For transcatheter-based minimally invasive procedures in structural heart disease ultrasound and X-ray are the two enabling imaging modalities. A live fusion of both real-time modalities can potentially improve the workflow and the catheter navigation by combining the excellent instrument imaging of X-ray with the high-quality soft tissue imaging of ultrasound. A recently published approach to fuse X-ray fluoroscopy with trans-esophageal echo (TEE) registers the ultrasound probe to X-ray images by a 2D-3D registration method which inherently provides a registration of ultrasound images to X-ray images. In this paper, we significantly accelerate the 2D-3D registration method in this context. The main novelty is to generate the projection images (DRR) of the 3D object not via volume ray-casting but instead via a fast rendering of triangular meshes. This is possible, because in the setting for TEE/X-ray fusion the 3D geometry of the ultrasound probe is known in advance and their main components can be described by triangular meshes. We show that the new approach can achieve a speedup factor up to 65 and does not affect the registration accuracy when used in conjunction with the gradient correlation similarity measure. The improvement is independent of the underlying registration optimizer. Based on the results, a TEE/X-ray fusion could be performed with a higher frame rate and a shorter time lag towards real-time registration performance. The approach could potentially accelerate other applications of 2D-3D registrations, e.g. the registration of implant models with X-ray images.

Paper Details

Date Published: 12 March 2013
PDF: 6 pages
Proc. SPIE 8671, Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling, 867111 (12 March 2013); doi: 10.1117/12.2007440
Show Author Affiliations
Markus Kaiser, Siemens AG (Germany)
Univ. Leipzig (Germany)
Matthias John, Siemens AG (Germany)
Anja Borsdorf, Siemens AG (Germany)
Peter Mountney, Siemens Corp. Technology (United States)
Razvan Ionasec, Siemens Corp. Technology (United States)
Alois Nöttling, Siemens AG (Germany)
Philipp Kiefer, Univ. Leipzig (Germany)
Jörg Seeburger, Univ. Leipzig (Germany)
Thomas Neumuth, Univ. Leipzig (Germany)


Published in SPIE Proceedings Vol. 8671:
Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling
David R. Holmes; Ziv R. Yaniv, Editor(s)

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