Kernel density correlation based non-rigid point set matching for statistical model-based 2D/3D reconstruction

Zheng, Guoyan (2011). Kernel density correlation based non-rigid point set matching for statistical model-based 2D/3D reconstruction. In: The 8th IEEE International Symposium on Biomedical Imaging: from Nano to Macro (ISBI) 2011 (pp. 1146-1149). Vancouver, Canada: Institute of Electrical and Electronics Engineers IEEE 10.1109/ISBI.2011.5872604

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This paper presents a kernel density correlation based nonrigid point set matching method and shows its application in statistical model based 2D/3D reconstruction of a scaled, patient-specific model from an un-calibrated x-ray radiograph. In this method, both the reference point set and the floating point set are first represented using kernel density estimates. A correlation measure between these two kernel density estimates is then optimized to find a displacement field such that the floating point set is moved to the reference point set. Regularizations based on the overall deformation energy and the motion smoothness energy are used to constraint the displacement field for a robust point set matching. Incorporating this non-rigid point set matching method into a statistical model based 2D/3D reconstruction framework, we can reconstruct a scaled, patient-specific model from noisy edge points that are extracted directly from the x-ray radiograph by an edge detector. Our experiment conducted on datasets of two patients and six cadavers demonstrates a mean reconstruction error of 1.9 mm

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB [discontinued]

UniBE Contributor:

Zheng, Guoyan

ISSN:

1945-7928

ISBN:

978-1-4244-4128-0

Publisher:

Institute of Electrical and Electronics Engineers IEEE

Language:

English

Submitter:

Factscience Import

Date Deposited:

04 Oct 2013 14:16

Last Modified:

05 Jan 2015 19:31

Publisher DOI:

10.1109/ISBI.2011.5872604

Web of Science ID:

000298849400263

BORIS DOI:

10.7892/boris.4672

URI:

https://boris.unibe.ch/id/eprint/4672 (FactScience: 209238)

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