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Proceedings Paper

A novel and stable approach to anatomical structure morphing for enhanced intraoperative 3D visualization
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Paper Abstract

The use of three dimensional models in planning and navigating computer assisted surgeries is now well established. These models provide intuitive visualization to the surgeons contributing to significantly better surgical outcomes. Models obtained from specifically acquired CT scans have the disadvantage that they induce high radiation dose to the patient. In this paper we propose a novel and stable method to construct a patient-specific model that provides an appropriate intra-operative 3D visualization without the need for a pre or intra-operative imaging. Patient specific data consists of digitized landmarks and surface points that are obtained intra-operatively. The 3D model is reconstructed by fitting a statistical deformable model to the minimal sparse digitized data. The statistical model is constructed using Principal Component Analysis from training objects. Our morphing scheme efficiently and accurately computes a Mahalanobis distance weighted least square fit of the deformable model to the 3D data model by solving a linear equation system. Relaxing the Mahalanobis distance term as additional points are incorporated enables our method to handle small and large sets of digitized points efficiently. Our novel incorporation of M-estimator based weighting of the digitized points enables us to effectively reject outliers and compute stable models. Normalization of the input model data and the digitized points makes our method size invariant and hence applicable directly to any anatomical shape. The method also allows incorporation of non-spatial data such as patient height and weight. The predominant applications are hip and knee surgeries.

Paper Details

Date Published: 12 April 2005
PDF: 8 pages
Proc. SPIE 5744, Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display, (12 April 2005); doi: 10.1117/12.595175
Show Author Affiliations
Kumar T. Rajamani, Univ. of Bern (Switzerland)
Miguel A. Gonzalez Ballester, Univ. of Bern (Switzerland)
Lutz-Peter Nolte, Univ. of Bern (Switzerland)
Martin Styner, Univ. of North Carolina/Chapel Hill (United States)


Published in SPIE Proceedings Vol. 5744:
Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display
Robert L. Galloway; Kevin R. Cleary, Editor(s)

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