Articulated Statistical Shape Model-Based 2D-3D Reconstruction of a Hip Joint View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2014

AUTHORS

S. Balestra , S. Schumann , J. Heverhagen , L. Nolte , G. Zheng

ABSTRACT

In this paper, reconstruction of three-dimensional (3D) patient-specific models of a hip joint from two-dimensional (2D) calibrated X-ray images is addressed. Existing 2D-3D reconstruction techniques usually reconstruct a patient-specific model of a single anatomical structure without considering the relationship to its neighboring structures. Thus, when those techniques would be applied to reconstruction of patient-specific models of a hip joint, the reconstructed models may penetrate each other due to narrowness of the hip joint space and hence do not represent a true hip joint of the patient. To address this problem we propose a novel 2D-3D reconstruction framework using an articulated statistical shape model (aSSM). Different from previous work on constructing an aSSM, where the joint posture is modeled as articulation in a training set via statistical analysis, here it is modeled as a parametrized rotation of the femur around the joint center. The exact rotation of the hip joint as well as the patient-specific models of the joint structures, i.e., the proximal femur and the pelvis, are then estimated by optimally fitting the aSSM to a limited number of calibrated X-ray images. Taking models segmented from CT data as the ground truth, we conducted validation experiments on both plastic and cadaveric bones. Qualitatively, the experimental results demonstrated that the proposed 2D-3D reconstruction framework preserved the hip joint structure and no model penetration was found. Quantitatively, average reconstruction errors of 1.9 mm and 1.1 mm were found for the pelvis and the proximal femur, respectively. More... »

PAGES

128-137

References to SciGraph publications

  • 2007. Deformable 2D-3D Registration of the Pelvis with a Limited Field of View, Using Shape Statistics in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2007
  • 2008. Spine Segmentation Using Articulated Shape Models in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2008
  • 2011-03. Femoroacetabular impingement: a review of diagnosis and management in CURRENT REVIEWS IN MUSCULOSKELETAL MEDICINE
  • 2010. Registration of a Statistical Shape Model of the Lumbar Spine to 3D Ultrasound Images in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2010
  • 2013-10. An Integrated System for 3D Hip Joint Reconstruction from 2D X-rays: A Preliminary Validation Study in ANNALS OF BIOMEDICAL ENGINEERING
  • 2013. Automated CT Segmentation of Diseased Hip Using Hierarchical and Conditional Statistical Shape Models in ADVANCED INFORMATION SYSTEMS ENGINEERING
  • 1999. Nonrigid 3-D/2-D Registration of Images Using Statistical Models in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI’99
  • Book

    TITLE

    Information Processing in Computer-Assisted Interventions

    ISBN

    978-3-319-07520-4
    978-3-319-07521-1

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-07521-1_14

    DOI

    http://dx.doi.org/10.1007/978-3-319-07521-1_14

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1052909732


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