Statistical Deformable Model-Based Reconstruction of a Patient-Specific Surface Model from Single Standard X-ray Radiograph

Zheng, Guoyan (2009). Statistical Deformable Model-Based Reconstruction of a Patient-Specific Surface Model from Single Standard X-ray Radiograph. In: 2009 International Conference on Computer Analysis of Images and Patterns. Lecture Notes in Computer Science: Vol. 5702 (pp. 672-679). Berlin, Heidelberg: Springer Berlin Heidelberg 10.1007/978-3-642-03767-2_82

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In this paper, we present a hybrid 2D-3D deformable registration strategy combining a landmark-to-ray registration with a statistical shape model-based 2D-3D reconstruction scheme, and show its application to reconstruct a patient-specific 3D surface model of the pelvis from single standard X-ray radiograph. The landmark-to-ray registration is used to find an initial scale and an initial rigid transformation between the X-ray image and the statistical shape model. The estimated scale and rigid transformation are then used to initialize the statistical shape model-based 2D-3D reconstruction scheme, which combines statistical instantiation and regularized shape deformation with an iterative image-to-model correspondence establishing algorithm. Quantitative and qualitative results of a feasibility study on clinical and cadaveric datasets are given, which indicate the validity of our approach.

Item Type:

Book Section (Book Chapter)

Division/Institute:

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

UniBE Contributor:

Zheng, Guoyan

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

ISBN:

978-3-642-03766-5

Series:

Lecture Notes in Computer Science

Publisher:

Springer Berlin Heidelberg

Language:

English

Submitter:

Guoyan Zheng

Date Deposited:

26 Jul 2017 14:13

Last Modified:

26 Jul 2017 14:13

Publisher DOI:

10.1007/978-3-642-03767-2_82

URI:

https://boris.unibe.ch/id/eprint/82209

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