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

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Computer Analysis of Images and Patterns (CAIP 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5702))

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Abstract

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.

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Zheng, G. (2009). Statistical Deformable Model-Based Reconstruction of a Patient-Specific Surface Model from Single Standard X-ray Radiograph. In: Jiang, X., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2009. Lecture Notes in Computer Science, vol 5702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03767-2_82

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  • DOI: https://doi.org/10.1007/978-3-642-03767-2_82

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03766-5

  • Online ISBN: 978-3-642-03767-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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