Approaching Spinal Kinematics using a Collision-Aware Articulated Deformable Model

  • Statistical Shape Models (SSMs) allow for a compact representation of shape and shape variation and they are a proven means for model-based 3D anatomy reconstruction from medical image data. In orthopaedics and biomechanics, SSMs are increasingly employed to individualize measurement data or to create individualized anatomical models. The human spine is a versatile and complex articulated structure and thus is an interesting candidate to be modeled using an advanced type of SSMs. For modeling and analysis of articulated structures, so called articulated SSMs (aSSMs) have been developed. However, a missing feature of aSSMs is the consideration of collisions in the course of individual fitting and articulation. The aim of this thesis is to develop an aSSM of two adjacent vertebrae that handles collisions between components correctly. The model will incorporate the two major aspects of variability: Shape of a single vertebra and the relative positioning of neighboring vertebrae. That way it becomes possible to adjust shape and articulation in view of a physically and geometrically plausible individualization. To be able to apply collision-aware aSSMs in simulation and optimisation in future work, the approach is based on a parallelized collision detection method employing Graphics Processing Units (GPUs).

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Metadaten
Author:Robert Joachimsky
Document Type:Master's Thesis
Tag:GPU-Accelerated Collision Detection; Spherical Shell; Spinal Kinematics; Spine Modeling
Granting Institution:Beuth Hochschule für Technik Berlin
Advisor:Stefan Zachow
Date of final exam:2019/07/31
Year of first publication:2019
Pagenumber:84