Model-Based Multiscale Detection of 3D Vessels

  • Authors:
  • K. Krissian;G. Malandain;N. Ayache;R. Vaillant;Y. Trousset

  • Affiliations:
  • -;-;-;-;-

  • Venue:
  • CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
  • Year:
  • 1998

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Abstract

In this paper, we present a new approach to segment vessels from 3D angiography of the brain. Our approach is based on a vessel model and uses a multiscale analysis in order to extract the vessel network surrounding an aneurysm. Our model allows us to choose a criterion based on the eigenvalues of the Hessian matrix for selecting a subset of interesting points near the vessel center. It also allows us to choose a good parameter for a 驴-normalization of the single scale response. The response at one scale is obtained by integmting along a circle the first derivative of the intensity in the mdial direction. Once the multiscale response is obtained, we create a smoothed skeleton of the vessels combined with a MIP or a volume rendering to enhance their visualization. The method has been tested on a large variety of 3-D images of the brain, with excellent results. Vessels of various size and contrast are detected with a remarkable robustness, and most junctions are preserved.