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Proceedings Paper

Gradient-based 3D-2D registration of cerebral angiograms
Author(s): Uroš Mitrović; Primož Markelj; Boštjan Likar; Zoran Miloševič 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 into the brain and into the aneurysm or AVM. Intra-interventional navigation utilizes digital subtraction angiography (DSA) to visualize vascular structures and X-ray fluoroscopy to localize the endovascular components. Due to the two-dimensional (2D) nature of the intra-interventional images, navigation through a complex three-dimensional (3D) structure is a demanding task. Registration of pre-interventional MRA, CTA, or 3D-DSA images and intra-interventional 2D DSA images can greatly enhance visualization and navigation. As a consequence of better navigation in 3D, the amount of required contrast medium and absorbed dose could be significantly reduced. In the past, development and evaluation of 3D-2D registration methods received considerable attention. Several validation image databases and evaluation criteria were created and made publicly available in the past. However, applications of 3D-2D registration methods to cerebral angiograms and their validation are rather scarce. In this paper, the 3D-2D robust gradient reconstruction-based (RGRB) registration algorithm is applied to CTA and DSA images and analyzed. For the evaluation purposes five image datasets, each comprised of a 3D CTA and several 2D DSA-like digitally reconstructed radiographs (DRRs) generated from the CTA, with accurate gold standard registrations were created. A total of 4000 registrations on these five datasets resulted in mean mTRE values between 0.07 and 0.59 mm, capture ranges between 6 and 11 mm and success rates between 61 and 88% using a failure threshold of 2 mm.

Paper Details

Date Published: 11 March 2011
PDF: 8 pages
Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 79621P (11 March 2011); doi: 10.1117/12.877541
Show Author Affiliations
Uroš Mitrović, 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 Miloševič M.D., Univ. of Ljubljana (Slovenia)
Franjo Pernuš, Univ. of Ljubljana (Slovenia)
Sensum Computer Vision Systems (Slovenia)

Published in SPIE Proceedings Vol. 7962:
Medical Imaging 2011: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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