Deformable modeling using a 3D boundary representation with quadratic constraints on the branching structure of the blum skeleton

  • Authors:

  • Paul A. Yushkevich;Hui Gary Zhang

  • Affiliations:

  • Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, Philadelphia;Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom

  • Venue:
  • IPMI'13 Proceedings of the 23rd international conference on Information Processing in Medical Imaging
  • Year:
  • 2013

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Abstract

We propose a new approach for statistical shape analysis of 3D anatomical objects based on features extracted from skeletons. Like prior work on medial representations [7,15,9], the approach involves deforming a template to target shapes in a way that preserves the branching structure of the skeleton and provides intersubject correspondence. However, unlike medial representations, which parameterize the skeleton surfaces explicitly, our representation is boundary-centric, and the skeleton is implicit. Similar to prior constrained modeling methods developed 2D objects [8] or tube-like 3D objects [13], we impose symmetry constraints on tuples of boundary points in a way that guarantees the preservation of the skeleton's topology under deformation. Once discretized, the problem of deforming a template to a target shape is formulated as a quadratically constrained quadratic programming problem. The new technique is evaluated in terms of its ability to capture the shape of the corpus callosum tract extracted from diffusion-weighted MRI.