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Proceedings Paper

3D-2D registration of cerebral angiograms based on vessel directions and intensity gradients
Author(s): Uroš Mitrovic; Žiga Špiclin; Darko Štern; Primož Markelj; Boštjan Likar; Zoran Miloševic M.D.; Franjo Pernuš
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Paper Abstract

Endovascular treatment of cerebral aneurysms and arteriovenous malformations (AVM) involves navigation of a catheter through the femoral artery and vascular system to the site of pathology. Intra-interventional navigation is done under the guidance of one or at most two two-dimensional (2D) X-ray fluoroscopic images or 2D digital subtracted angiograms (DSA). Due to the projective nature of 2D images, the interventionist needs to mentally reconstruct the position of the catheter in respect to the three-dimensional (3D) patient vasculature, which is not a trivial task. By 3D-2D registration of pre-interventional 3D images like CTA, MRA or 3D-DSA and intra-interventional 2D images, intra-interventional tools such as catheters can be visualized on the 3D model of patient vasculature, allowing easier and faster navigation. Such a navigation may consequently lead to the reduction of total ionizing dose and delivered contrast medium. In the past, development and evaluation of 3D-2D registration methods for endovascular treatments received considerable attention. The main drawback of these methods is that they have to be initialized rather close to the correct position as they mostly have a rather small capture range. In this paper, a novel registration method that has a higher capture range and success rate is proposed. The proposed method and a state-of-the-art method were tested and evaluated on synthetic and clinical 3D-2D image-pairs. The results on both databases indicate that although the proposed method was slightly less accurate, it significantly outperformed the state-of-the-art 3D-2D registration method in terms of robustness measured by capture range and success rate.

Paper Details

Date Published: 14 February 2012
PDF: 12 pages
Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83141T (14 February 2012); doi: 10.1117/12.910904
Show Author Affiliations
Uroš Mitrovic, Univ. of Ljubljana (Slovenia)
Žiga Špiclin, Univ. of Ljubljana (Slovenia)
Darko Štern, Univ. of Ljubljana (Slovenia)
Primož Markelj, Univ. of Ljubljana (Slovenia)
Sensum Computer Vision Systems (Slovenia)
Boštjan Likar, Univ. of Ljubljana (Slovenia)
Sensum Computer Vision Systems (Slovenia)
Zoran Miloševic M.D., Univ. of Ljubljana (Slovenia)
Franjo Pernuš, Univ. of Ljubljana (Slovenia)
Sensum Computer Vision Systems (Slovenia)


Published in SPIE Proceedings Vol. 8314:
Medical Imaging 2012: Image Processing
David R. Haynor; Sébastien Ourselin, Editor(s)

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